Cardiovascular assist system that quantifies heart function and facilitates heart recovery

ABSTRACT

The systems, devices, and methods presented herein use a heart pump to obtain measurements of cardiovascular function. The heart pumps described herein can operate in parallel with and unload the heart. The system can quantify the functioning of the native heart by measuring certain parameters/signals such as pressure or motor current, then calculate and display one or more metrics of cardiovascular function. These metrics, such as left ventricular end diastolic pressure (LVEDP), left ventricular pressure, and contractility, provide valuable information to a user regarding a patient&#39;s state of heart function and recovery.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. provisional application No.62/396,628, filed Sep. 19, 2016, the content of which is herebyincorporated herein by reference in its entirety.

BACKGROUND

Cardiovascular (CV) diseases are a leading cause of morbidity,mortality, and burden on healthcare around the world, with about 7million cases of heart failure and many more cases of myocardialinfarction in the United States alone. Acute and chronic CV conditionsreduce quality of life and life expectancy. A variety of treatmentmodalities have been developed for CV disease, ranging frompharmaceuticals to mechanical devices and finally transplantation.Temporary cardiac support devices, such as ventricular assist devices,provide hemodynamic support, and facilitate heart recovery.

There are many types of temporary cardiac assist devices with varyingdegrees of support and invasiveness, from intra-aortic balloon pumps(IABP) to extracorporeal membrane oxygenation (ECMO) devices to leftventricular assist devices (LVAD) implanted surgically. These devicescommonly reside outside the ventricle or bypass the ventricle, and donot work in parallel with or directly support heart function. They alsodo not provide clinicians with quantifiable metrics that can guide thelevel of cardiac support that is required for a particular patient. Someventricular assist devices are percutaneously inserted into the heartand can run in parallel with the native heart to supplement cardiacoutput, such as the IMPELLA® family of devices (Abiomed, Inc., DanversMass.).

The amount of support (e.g., volumetric flow rate of blood delivered bythe pumping device) and/or the duration of support each patient needscan vary. It has been suggested that variations in the motor currentrequired to maintain a rotor speed can be utilized to understandplacement of the pump or pump function, but these proposals have fallenshort of usefully processing the motor current data to measure cardiacfunction. For example, U.S. Pat. No. 6,176,822 describes measuring motorcurrent to aid in proper positioning of the pump, and U.S. Pat. No.7,022,100 mentions calculating blood pressure based on the relationshipbetween the torque and motor current of a motor used to drive the rotor.However, the motor current alone provides only limited insights into apatient's overall cardiac function, and existing measures such as aorticpressure do not correlate to a patient's overall cardiac function.Accordingly, there is a need to more directly and quantitativelyestimate metrics of cardiac function to aid clinicians in determininghow much support a device should deliver or when to terminate use of acardiac assist device.

SUMMARY

The systems, devices, and methods described herein enable a supportdevice residing within an organ to assess that organ's function. Inparticular, the systems, devices, and methods enable cardiac assistdevices, such as percutaneous ventricular assist devices, to be used toassess the function of the heart based on a measurement of deviceperformance and measurement of one or more hemodynamic parameters.Assessing the function of the heart using a cardiac assist device canallow the degree of/level of support provided by the assist device(e.g., flow rate of blood pumped by a pumping device) to be tailored toa particular patient's needs. For example, changes in device performance(or absolute performance of the device) can be detected and the detectedperformance used to determine whether and the extent to which apatient's heart is deteriorating or improving. Based on the detectedperformance, the degree of support is adjusted. For example, the degreeof support can be increased when a patient's heart function isdeteriorating, or the degree of support can be decreased when apatient's heart function is recovering and returning to a baseline ofnormal heart function. This allows the clinician to respond to changesin heart function to promote heart recovery, which can allow the patientto be gradually weaned off of the therapy. Furthermore, assessment ofthe heart function for greater understanding of cardiac function canindicate when it is appropriate to terminate use of the cardiac assistdevice. Although some embodiments presented herein are directed tocardiovascular assist devices implanted across the aortic valve andresiding partially in the left ventricle, the concepts can be applied todevices in other regions of the heart, the cardiovascular system, or thebody.

Moreover, the cardiac assist devices herein can continuously or nearlycontinuously monitor and assess cardiac function while the device is inthe patient. This can be advantageous over methods that only estimatecardiac function at specific intervals of time. For example, continuousmonitoring may allow real time detection of cardiac deterioration, whichis more rapid than prior art methods. The cardiac devices can beinserted without destruction of injury of organs using minimallyinvasive procedures. Additionally, if the cardiac assist device isalready in the patient, the cardiac function can be measured withouthaving to introduce an additional catheter into a patient.

The systems, devices, and methods presented herein determine heartfunction parameters indicative of native heart function frommeasurements of intravascular pressure and pump parameters (a“parameter” can represent a signal and/or operating state of thecardiovascular system and/or the heart pump). Cardiac function can bequantified in several different ways using the devices and techniquespresented herein, including one or more of left ventricular enddiastolic pressure (LVEDP), contractility, stroke volume, ejectionfraction, chamber pressure, stroke work, cardiac output, cardiac poweroutput, preload state, afterload state, heart rate, heart recovery, flowload state, variable volume load state, and/or cardiac cycle flow state.In some applications, such heart parameters are determined based in parton hysteresis between pressure measurements (e.g., differential pressurebetween aortic pressure and left ventricular pressure, or the aorticpressure, or other pressure measured in the vasculature or within adevice inserted within the vasculature) and motor current measurementsthat allow the detection of the phase of the cardiac cycle correspondingto a given pair of pressure and current measurements. From thesemeasurements a user can determine important information about heartfunction, and in some cases information about the cardiac assist deviceperformance, including the occurrence of suction events.

In one aspect, a heart pump system includes a catheter, a motor, a rotoroperatively coupled to the motor, and a pump housing at least partiallysurrounding the rotor so that actuating the motor drives the rotor andpumps blood through the pump housing. The heart pump system alsoincludes a sensor which detects a hemodynamic parameter over time, and acontroller. The controller detects a motor parameter over time, receivesan input from the sensor of the detected hemodynamic parameter overtime, and determines a relationship between the detected hemodynamicparameter and the motor parameter, such as the relationship between thehemodynamic parameter measured over time and the motor parametermeasured over time. For example, the controller may store the detectedmotor parameter and hemodynamic parameters in a memory and may associatethe motor parameter and hemodynamic parameter data so that they arematched in time. The controller characterizes the relationship betweenthe detected hemodynamic parameter and the motor parameter using apolynomial best fit algorithm, and stores the characterized relationshipin a memory. For example, the controller may characterize therelationship by fitting all or a portion of the data (e.g., a portion ofthe hemodynamic parameter data, such as pressure measurements, and aportion of the motor parameter data, such as motor current measurements)to an appropriate equation, such as an elliptical fit, a polynomialequation, or Euler's equation.

In some implementations, the motor parameter is current delivered to themotor, power delivered to the motor, or motor speed. In someimplementations, the controller determines at least one cardiovascularmetric by extracting an inflection point, a local slope change, or acurvature change from the characterized relationship between thedetected hemodynamic parameter and the motor parameter. In someimplementations, the at least one cardiovascular metric is at least oneof contractility, stroke volume, ejection fraction, chamber pressure,stroke work, cardiac output, cardiac power output, left ventricularpressure, preload state, afterload state, heart rate, heart recovery,flow load state, variable volume load state, cardiac cycle volume loadstate, or cardiac cycle flow state. In some implementations, the atleast one cardiovascular metric is the left ventricular end diastolicpressure (LVEDP).

In some implementations, the hemodynamic parameter is aortic pressureand the motor parameter is current, and characterizing the relationshipincludes fitting an equation to at least a portion of data representingthe measured current and a pressure head calculated from the measuredcurrent and aortic pressure. In some implementations, the controllerdetermines an LVEDP point from the equation fit to at least a portion ofthe current and pressure head data, and accesses a look-up table todetermine an actual LVEDP value from the LVEDP point in the pressurehead data. In some implementations, determining an LVEDP point includesidentifying an inflection point, a local slope change, or a curvaturechange in the equation fit to at least a portion of the current andpressure head data.

In some implementations, the controller determines a cardiac cycle phasefrom the relationship between the detected hemodynamic parameter and themotor parameter. In some implementations, the controller describes ahysteresis curve based on the relationship between the detectedhemodynamic parameter and the motor parameter, and selects a sample timeon the hysteresis curve corresponding to the cardiac cycle phase.

In some implementations, determining the cardiac cycle phase includesdetecting that the cardiac cycle phase is in diastolic relaxation whenthe sample time corresponds to a segment of the hysteresis curvecorresponding to an increasing pressure head, detecting that the cardiaccycle phase is in diastolic filling when the sample time corresponds toa segment of the hysteresis curve corresponding to a decreasing pressurehead following diastolic relaxation to appoint distinguished by a rapidchange in slope or curvature, or identification of the inflection point,or detecting that the cardiac cycle phase is in systole when the sampletime corresponds to a segment of the hysteresis curve having adecreasing pressure head from the inflection point to a minimum pressurehead.

In some implementations, the motor parameter and hemodynamic parameterare detected over a portion of a cardiac cycle. In otherimplementations, the motor parameter and hemodynamic parameter aredetected over one or more cardiac cycles. In some implementations, themotor maintains a substantially constant speed of the rotor duringactuation of the rotor. In some implementations, the controller storesthe at least one cardiovascular metric in a memory with a previouslydetermined at least one cardiovascular metric. In some implementations,the heart pump system also includes an integrated motor positioned nearthe distal end of the catheter proximate the heart pump.

In another aspect, a heart pump system includes a catheter, a motor, arotor operatively coupled to the motor, and a pump housing at leastpartially surrounding the rotor so that actuating the motor drives therotor and pumps blood through the pump housing. The heart pump systemalso includes a pressure sensor which detects an aortic pressure overtime, and a controller. The controller detects a motor parameter overtime, receives the aortic pressure over time from the sensor, stores arelationship between the motor parameter and the aortic pressure in thememory, determines a time period in which an inflection point indicativeof LVEDP can be found, and identifies the inflection point in the aorticpressure based on the determined time period.

In some implementations, determining a time period in which aninflection point indicative of the LVEDP can be found includesidentifying a time period in which the received motor parameter changes.In some implementations, the controller also determines the LVEDP from adynamic curve look-up table stored in the memory based on the inflectionpoint in the aortic pressure. In some implementations, the controllerreceives an ECG signal, and determining a time period in which aninflection point indicative of LVEDP can be found includes identifying atime period in which the ECG signal indicates an end cycle of diastole.

In some implementations, the motor parameter is one of motor current,change in motor current, variability of motor current, and a netintegrated area of motor current and pressure. In some implementations,the controller also determines a cardiac cycle phase from therelationship between the motor parameter and the aortic pressure, andthe cardiac cycle phase is determined using one or more of ECG data, ahemodynamic parameter, the motor parameter and a motor speed, and/or aslope of the aortic pressure. In some implementations, the motor isconfigured to maintain a substantially constant rotor speed duringactuation of the rotor. In some implementations, the heart pump furthercomprises an integrated motor sized and configured for insertion into apatient's vasculature.

In another aspect, a heart pump system includes a heart pump and anelectronic controller. The heart pump includes a motor, a rotoroperatively coupled to the motor, and a sensor of hemodynamicparameters. The controller is configured to measure a motor parameter,for example current delivered to the motor, power delivered to themotor, or motor speed, and to measure the hemodynamic parameter overtime using the sensor. The controller is configured to determine anddescribe a hysteresis curve based on inputs representative of the motorparameter and inputs representative of the hemodynamic parameter overtime, determined according to a best fit algorithm or other suitableprocessing algorithm, and to scale the fitted hysteresis curve based ona measured patient cardiac parameter, for example aortic pressure, todetermine a left ventricular pressure.

In some implementations, the controller is configured to determine atleast one cardiovascular metric by extracting an inflection point valuefrom a scaled hysteresis curve. In some adaptations, the at least onecardiovascular metric is the left ventricular end diastolic pressure. Insome implementations, determining or characterizing the hysteresis curveincludes selecting a polynomial expression to fit the hysteresis curveand using the controller to process data representative of motorparameter and hemodynamic parameter (e.g., from sensor measurements) tocalculate the curve. For example, data indicative of motor parametersand measured hemodynamic parameter may be stored in the controller asarrays of data in tables within a database in a memory or in a server,and the controller may access such data tables to obtain such data tocalculate the hysteresis curve. The stored data can be accessed by thecontroller or by a user at a later time.

In some implementations, the hemodynamic parameter is pressure head. Insome implementations, the at least one cardiovascular metric is at leastone of contractility, stroke volume, ejection fraction, chamberpressure, stroke work, cardiac output, cardiac power output, leftventricular end diastolic pressure, preload state, afterload state,heart rate, heart recovery, flow load state, variable volume load state,cardiac cycle volume load state, and/or cardiac cycle flow state. Insome implementations, the motor maintains a constant speed of the rotorduring the measurement of the motor parameter.

In some implementations, the controller is further configured todetermine, from the hysteresis curve, a heart phase. In someimplementations, the heart phase is determined using one or more of ECGdata, pressure measured at the pressure sensor, the motor parameter andmotor speed, the aortic pressure slope, and a respiratory variation. Insome implementations, determining the heart phase includes selecting,based on the measurement of the motor parameter and a pressure head at asample time, a segment of the hysteresis curve to which the sample timecorresponds, the segment corresponding to one of relaxation,contraction, ejection, and filling. In some implementations, determiningthe heart phase further includes detecting that the heart phase isdiastole when the sample time corresponds to a segment of the hysteresiscurve having a high pressure, and detecting that the heart phase issystole when the sample time corresponds to a segment of the hysteresiscurve having a low pressure.

In another aspect, a heart pump system includes a motor, a rotoroperatively coupled to the motor, a pressure sensor, and a controller.The controller is configured to measure a motor parameter, measurepressure head over time, using the pressure sensor, describe ahysteresis curve based on hysteresis between the motor parameter and thepressure head over time according to a best fit algorithm, scale thefitted hysteresis curve based on a measured aortic pressure to determinea left ventricular pressure, determine at least one cardiovascularmetric by extracting an inflection point from the scaled hysteresiscurve, and display the at least one cardiovascular metric on a displayscreen of the controller.

In some implementations, the at least one cardiovascular metric is theleft ventricular end diastolic pressure. In some implementations,describing the hysteresis curve includes choosing a polynomialexpression to fit the hysteresis curve. In some implementations, the atleast one cardiovascular metric is at least one of contractility, strokevolume, ejection fraction, chamber pressure, stroke work, cardiacoutput, cardiac power output, left ventricular end diastolic pressure,preload state, afterload state, heart rate, heart recovery, flow loadstate, variable volume load state, cardiac cycle volume load state,and/or cardiac cycle flow state. In some implementations, the motorparameter is motor current, change in motor current, variability ofmotor current, or the net integrated area of motor current and pressure.In some implementations, the motor maintains a constant rotor speedduring the measurement of the motor parameter.

In some implementations, the controller is further configured todetermine a heart phase from the hysteresis curve. In someimplementations, the heart phase is determined using one or more of ECGdata, pressure measured at the pressure sensor, the motor parameter andmotor speed, the aortic pressure slope, and a respiratory variation. Insome implementations, determining the heart phase includes accessing thehysteresis curve, selecting, based on the measurement of the motorparameter and the pressure head and a sample time, a segment of thecurve to which the sample time corresponds, and determining, based onthe segment, a corresponding heart phase of relaxation, contraction,ejection, or filling.

In some implementations, the motor has a diameter of less than about 21French. In some implementations, the at least one heart metric is atleast one of contractility, stroke volume, ejection fraction, chamberpressure, stroke work, cardiac output, cardiac power output, leftventricular end diastolic pressure, preload state, afterload state,heart rate, heart recovery, flow load state, variable volume load state,cardiac cycle volume load state, and/or cardiac cycle flow state. Insome implementations, the controller is configured to automaticallyadjust a level of support provided by the heart pump when the at leastone heart metric indicates changes in a patient's heart state, whereinthe patient's heart state is defined by at least one of changes incontractility, changes in volume load, changes in preload, changes inafterload, changes in heart rate, and changes in pulse pressure. In someimplementations, the controller is configured to automate a level ormethod of support provided by the heart pump to augment and improvenative heart functions, wherein automating the level or method ofsupport comprises at least one of changing a volume flow of blooddelivered by the heart pump, changing a frequency and/or amplitude ofautomated blood flow pulsation, and changing a rotational speed of therotor. In some implementations, the motor maintains a constant motorspeed during the measurement of the motor parameter.

In some implementations, determining the heart phase includes accessinga plot of the pressure as a function of the motor parameter wherein theplot forms a hysteresis loop, and using the measurement of the motorparameter and the pressure at the sample time to identify a segment ofthe hysteresis loop to which a sample time corresponds, wherein eachsegment corresponds to a heart phase. In some implementations, the heartphase is determined using ECG data. In some implementations, the heartphase is determined using the pressure measured at the pressure sensor.In some implementations, determining the heart phase also includesdetecting that the heart phase is diastole if the sample timecorresponds to a segment of the hysteresis loop having high pressure,and detecting that the heart phase is systole if the sample timecorresponds to a segment of the hysteresis loop having low pressure.

In some implementations, the controller is configured to generate a plotof the pressure and motor parameter measurements, wherein the motorparameter is a first coordinate of the plot and the pressure is a secondcoordinate of the plot, or to monitor the relationship of a motorparameter and pressure system. In some implementations, the blood pumpis percutaneous. In some implementations, the motor is implantable. Insome implementations, the heart pump system is configured such that thepressure sensor is positioned within the aorta when the rotor is placedin the aorta. In some implementations, the heart pump system is anintravascular heart pump system.

In another aspect, a heart pump system includes a heart pump and acontroller. The heart pump includes a motor, a rotor operatively coupledto the motor, and a sensor for a hemodynamic parameter, for example apressure sensor. The controller is configured to measure a motorparameter and measure hemodynamic parameter by the sensor, determine aheart phase, determine at least one heart metric indicative of cardiacfunction and display the at least one heart metric on a display screenof the controller. For example, the controller may be configured tomeasure the motor parameter of current delivered to the motor or powerdelivered to the motor, measure the pressure at a pressure sensor,determine a heart phase, determine at least one heart metric indicativeof cardiac function and display the at least one heart metric on adisplay screen of the controller. The heart metric indicative of cardiacfunction may be determined using a predetermined pressure-motor curve,and the determination of the at least one heart metric may be based onhysteresis between the motor parameter and the pressure.

In some implementations, the measured pressure is one of aorticpressure, or a difference in pressure between aortic pressure and leftventricular pressure. In some implementations, the at least one heartmetric is at least one of contractility, stroke volume, ejectionfraction, chamber pressure, stroke work, cardiac output, cardiac poweroutput, left ventricular end diastolic pressure, preload state,afterload state, heart rate, heart recovery, flow load state, variablevolume load state, cardiac cycle volume load state, and/or cardiac cycleflow state. In some implementations, the controller is configured toautomatically adjust a level of support provided by the heart pump whenthe at least one heart metric indicates changes in a patient's heartstate, wherein the patient's heart state is defined by at least one ofchanges in contractility, changes in volume load, changes in preload,changes in afterload, changes in heart rate, and changes in pulsepressure. In some implementations, the controller is configured toautomate a level or method of support provided by the heart pump toaugment and improve native heart functions, wherein automating the levelor method of support comprises at least one of changing a volume flow ofblood delivered by the heart pump, changing a frequency and/or amplitudeof automated blood flow pulsation, and changing a rotational speed ofthe rotor. In some implementations, the motor maintains a constant motorspeed during the measurement of the motor parameter.

In some implementations, determining the heart phase includes accessinga plot of the pressure as a function of the motor parameter wherein theplot forms a hysteresis loop, and using the measurement of the motorparameter and the pressure at the sample time to determine a segment ofthe hysteresis loop to which a sample time corresponds, wherein eachsegment corresponds to a heart phase. In some implementations, the heartphase is determined using ECG data. In some implementations, the heartphase is determined using the pressure measured at the pressure sensor.In some implementations, determining the heart phase also includesdetecting that the heart phase is diastole if the sample timecorresponds to a segment of the hysteresis loop having high pressure,and detecting that the heart phase is systole if the sample timecorresponds to a segment of the hysteresis loop having low pressure.

In some implementations, the controller is configured to generate a plotof the pressure and motor parameter measurements, wherein the motorparameter is a first coordinate of the plot and the pressure is a secondcoordinate of the plot, or to monitor the relationship of a motorparameter and pressure system. In some implementations, the blood pumpis percutaneous. In some implementations, the motor is implantable. Insome implementations, the heart pump system is configured such that thepressure sensor is positioned within the aorta when the rotor is placedin the aorta. In some implementations, the motor parameter is one ofmotor current, change in motor current, variability of motor current,and the net integrated area of motor current and pressure. In someimplementations, the heart pump system is an intravascular heart pumpsystem.

In another aspect, a heart pump system includes a heart pump and acontroller. The heart pump includes a motor, a rotor operatively coupledto the motor, and a pressure sensor. The controller is configured tomeasure a motor parameter where the motor parameter is current deliveredto the motor or power delivered to the motor, measure the pressure atthe pressure sensor, determine a heart phase, determine at least oneheart metric indicative of cardiac function, determine at least onerecommendation of a change for operating a heart pump based on the atleast one heart metric, and display the at least one recommendation on adisplay screen of the controller. The heart metric indicative of cardiacfunction is determined using a predetermined pressure-motor curve, andthe determination of the at least one heart metric is based onhysteresis between the motor parameter and the pressure.

In some implementations, at least one recommendation includes changing arotational speed of the rotor, changing power delivered to the motor,and/or removing the heart pump from a patient. In some implementations,the at least one heart metric is at least one of contractility, strokevolume, ejection fraction, chamber distention, chamber hypertrophy,chamber pressure, stroke work, cardiac output, cardiac power output,left ventricular end diastolic pressure, preload state, afterload state,heart rate, and heart recovery. In some implementations, the controlleris configured to automatically adjust a level of support provided by theheart pump when the at least one heart metric indicates changes in apatient's heart state, wherein the patient's heart state is defined byat least one of changes in contractility, changes in volume load,changes in preload, changes in afterload, changes in heart rate, andchanges in pulse pressure. In some implementations, the controller isconfigured to automate a level or method of support provided by theheart pump to augment and improve native heart functions, whereinautomating the level or method of support comprises at least one ofchanging a volume flow of blood delivered by the heart pump, changing afrequency and/or amplitude of automated blood flow pulsation, andchanging a rotational speed of the rotor. In some implementations, themotor maintains a constant motor speed during the measurement of themotor parameter.

In some implementations, determining the heart phase includes accessinga plot of the pressure as a function of the motor parameter wherein theplot forms a hysteresis loop, and using the measurement of the motorparameter and the pressure at the sample time to identify a segment ofthe hysteresis loop to which a sample time corresponds, wherein eachsegment corresponds to a heart phase. In some implementations, the heartphase is determined using ECG data. In some implementations, the heartphase is determined using the pressure measured at the pressure sensor.In some implementations, determining the heart phase also includesdetecting that the heart phase is diastole if the sample timecorresponds to a segment of the hysteresis loop having high pressure,and detecting that the heart phase is systole if the sample timecorresponds to a segment of the hysteresis loop having low pressure.

In some implementations, the controller is configured to generate a plotof the pressure and motor parameter measurements, wherein the motorparameter is a first coordinate of the plot and the pressure is a secondcoordinate of the plot, or to monitor the relationship of a motorparameter and pressure system. In some implementations, the blood pumpis percutaneous. In some implementations, the motor is implantable. Insome implementations, the heart pump system is configured such that thepressure sensor is positioned within the aorta when the rotor is placedin the aorta. In some implementations, the motor parameter is one ofmotor current, change in motor current, variability of motor current,and the net integrated area of motor current and pressure. In someimplementations, the heart pump system is an intravascular heart pumpsystem.

In another aspect, a heart pump system includes a heart pump and acontroller. The heart pump includes a rotor, a motor coupled to therotor, a blood inlet, and a pressure sensor. The controller is incommunication with the motor and the pressure sensor. The controller isconfigured to measure a motor parameter at a sample time, measurepressure at the pressure sensor at the sample time, and determinewhether the blood inlet is occluded based on the measurement of themotor parameter and the pressure at the sample time, wherein occlusionof the blood inlet is determined using hysteresis in the measurement ofthe motor parameter and the pressure at the pressure sensor. In someimplementations, the controller is configured to display a warningparameter in response to determining that the blood inlet is occluded.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects and advantages will be apparent uponconsideration of the following detailed description, taken inconjunction with the accompanying drawings, in which like referencecharacters refer to like parts throughout, and in which:

FIG. 1 shows a prior art catheter-based intravascular heart pump systemlocated in a heart;

FIG. 2 shows a prior art LVAD heart pump system located in the heart;

FIG. 3 shows an illustrative heart pump system configured to estimatecardiovascular parameters according to certain implementations;

FIG. 4 shows a process for determining a heart parameter indicative ofheart function according to certain implementations;

FIG. 5 shows a process for calculating metrics of heart functionaccording to certain implementations;

FIG. 6 shows a process of determining LVEDP from a measured motorparameter signal and a sensor signal using various gating processes,according to certain implementations.

FIG. 7 shows a process of applying a gating algorithm to determine theLVEDP;

FIG. 8 shows a plot of aortic pressure, left ventricular pressure, andmotor current over time;

FIG. 9 shows a process of applying a gating algorithm based on ECG datato determine the LVEDP;

FIG. 10 shows a plot of LVEDP as measured and as calculated byalgorithms over time;

FIG. 11 shows a plot of the LVEDP calculated from patient dataillustrating the accuracy of the determined LVEDP using a gating method;

FIG. 12 shows a plot of pressure head as a function of motor currentbased on data from a porcine animal model;

FIG. 13 shows a plot of pressure head as a function of motor currentfrom a porcine animal model with spline curves fit to the regions of thehysteresis loop;

FIG. 14 shows a plot of pressure head as a function of a hysteresisparameter after a hysteresis gate has been applied to segment the datagathered from a porcine animal model;

FIG. 15 shows a plot of pressure head as a function of a motorhysteresis parameter;

FIG. 16 shows a plot of pressure head as a function of motor currentbefore and after administration of a beta-blocker in a porcine animalmodel;

FIG. 17 shows a smoothed curve of a plot of pressure head as a functionof motor current;

FIG. 18a shows a plot of pressure head as a function of motor currentbefore and during transitioning of a myocardial infarction;

FIG. 18b shows a plot of heart power index and motor current as afunction of samples measured over time before and during a myocardialinfarction;

FIG. 19 shows a series of plots of mock loop data with variedcontractility under a constant load;

FIG. 20a shows an exemplary user interface for a heart pump controllerdisplaying measurements over time;

FIG. 20b shows an exemplary user interface for a heart pump controlleraccording to certain implementations; and

FIG. 21 shows a process for detecting suction in an intravascular heartpump and determining the cause of the suction according to certainimplementations.

DETAILED DESCRIPTION

To provide an overall understanding of the systems, method, and devicesdescribe herein, certain illustrative embodiments will be described.Although the embodiments and features described herein are specificallydescribed for use in connection with a percutaneous heart pump system,it will be understood that all the components and other featuresoutlined below may be combined with one another in any suitable mannerand may be adapted and applied to other types of cardiac therapy andcardiac assist devices, including cardiac assist devices implanted usinga surgical incision, and the like.

The systems, devices, and methods described herein enable a supportdevice residing completely or partially within an organ to assess thatorgan's function. In particular, the systems, devices, and methodsenable cardiac assist devices, such as percutaneous ventricular assistdevices, to be used to assess the function of the heart. For example, acardiac state can be measured or monitored by tracking theelectro-mechanical controller values of a ventricular assist devicepositioned in the heart of a patient. Because the device maintains aconstant rotor speed by varying the motor current to respond to changesin the pressure in the chambers of the heart, a continuous measurementof a motor parameter and a pressure, for example the motor current andthe aortic pressure, provides continuous, real-time, and precisedetermination of cardiac function, for example a left ventricularpressure. Assessing the function of the heart using a cardiac assistdevice can alert health professionals of changes in cardiac function andallow the degree of/level of support provided by the assist device(i.e., flow rate of blood pumped by the device) to be tailored to aparticular patient's needs. For example, the degree of support can beincreased when a patient's heart function is deteriorating, or thedegree of support can be decreased when a patient's heart function isrecovering and returning to a baseline of normal heart function. Thiscan allow the device to dynamically respond to changes in heart functionto promote heart recovery and can allow the patient to be graduallyweaned off of the therapy. Furthermore, assessment of the heart functioncan indicate when it is appropriate to terminate use of the cardiacassist device. Although some embodiments presented herein are directedto cardiac assist devices implanted across the aortic valve and residingpartially in the left ventricle, the concepts can be applied to devicesin other regions of the heart, the cardiovascular system, or the body.

Moreover, the cardiac assist devices herein can continuously or nearlycontinuously monitor and assess cardiac function while the device is inthe patient. This can be advantageous over methods that can onlyestimate cardiac function at specific intervals of time. For example,continuous monitoring may allow more rapid detection of cardiacdeterioration. Additionally, if the cardiac assist device is already inthe patient, the cardiac function can be measured without having tointroduce an additional catheter into a patient.

Assessment of cardiac function by the cardiac assist devices presentedherein is enabled, at least in part, by the minimally-invasive nature ofthe cardiac assist devices. Unlike some invasive cardiac assist deviceswhich shunt blood out of the heart, the cardiac assist devices presentedherein reside within the heart and work in parallel with nativeventricular function. This allows the cardiac assist devices presentedherein to be sensitive enough to detect native ventricular functionunlike some more invasive devices. Thus, the systems, devices, andmethods enable the use of cardiac assist devices not only as supportdevices, but also as diagnostic and prognostic tools. The cardiac assistdevices can essentially function as active catheters that extractinformation about cardiac function by hydraulically coupling with theheart. In some implementations, the cardiac assist devices operate at aconstant level (e.g., constant rotational speed of a rotor), while powerdelivered to the assist device is measured. In certain implementations,the speed of the rotor of the cardiac assist device may be varied (e.g.,as a delta, step, or ramp function) to further probe the native heartfunction.

Heart function parameters indicative of native heart function can bedetermined from measurements of intravascular and/or ventricularpressure and pump parameters/signals (a “parameter” can represent asignal and/or operating state of the heart pump). For example, the heartparameters can be determined from aortic pressure and pump motorcurrent. This determination can be made using a model of the combinedheart and heart pump system. In one method of cardiac functiondetermination, the model includes accessing predetermined curves. Thismodel may be a look-up table or a predetermined/normalized pumpperformance curve or calibration curve or any other suitable model. Alook-up table may include a set of curves showing the power required tomaintain a rotational speed and pressure head are determined as afunction of pump flow, and a set of curves relating the pressure headand the flow characteristics of the heart are also determined. Forexample, a look-up table may indicate that a particular aortic pressureand motor current corresponds to a particular left ventricular enddiastolic pressure (LVEDP). In another method of cardiac functiondetermination, the performance of the pump is represented by showing thepressure head as a function of the pump's motor current draw, thecurrent draw acting as a surrogate for the power or load on the pump.The relationship between the motor current draw and the pressure headduring the cardiac cycle describes a hysteresis curve or loop. Cardiacstate and functions, including LVP and LVEDP can be extracted from therelationship between the motor current draw and pressure head. Besidesor in addition to LVEDP, cardiac function can be quantified in severaldifferent ways using the cardiac assist devices presented herein. Forexample, heart function can be expressed as contractility, strokevolume, ejection fraction, chamber pressure, stroke work, cardiacoutput, cardiac power output, LVEDP, preload state, afterload state,heart rate, and/or heart recovery.

To accurately determine these heart parameters, hysteresis between thepressure measurements (e.g., difference between aortic pressure and leftventricular pressure, or the aortic pressure alone) and the motorcurrent measurements may be taken into account. This hysteresis can beaccounted for by detecting the phase of the cardiac cycle correspondingto a given pair of pressure and current measurements. This can be doneusing at least two methods that differentiate diastolic filling from theother phases of the cardiac cycle. Both methods identify critical pointswhich indicate the beginning and end of diastolic filling. The firstmethod uses the aortic pressure waveform and identifies keycharacteristics in the curve, such as the dicrotic notch, to indicatethe beginning of diastolic filling. This method can also use thebeginning of aortic filling to indicate the end of diastolic ventricularfilling. The second method uses ECG data timed with the pressuretracings to identify two key characteristics that demarcate diastolicfilling. These characteristics are preferably the beginning of the QRScomplex and the end of the T-wave. If there is noise in the signal, itcan be more reliable to detect the peak of the QRS complex (the R-wave)and the peak of the T-wave. Furthermore, in some implementations, thehysteresis between the pressure and motor parameter measurements canitself be used to determine the phase of the cardiac cycle.

The systems, devices, and methods presented herein also account forvariations in heart rate. If unaccounted for, changes in heart rate mayaffect the resolution of the waveforms and hence the accuracy of theheart parameter estimations. For example, a higher heart rate at a givensampling frequency results in fewer samples per cardiac cycle. Thenumber of samples per cardiac cycle is critical for capturing keyfeatures used to account for hysteresis, such as the dicrotic notch, aswell as key points in the pressure waveform such as the LVEDP. If thesampling number is too low, these features can be missed since thenumber of samples in the region of interest decrease. However, thesensitivity to heart rate can be reduced or eliminated in someimplementations by not performing waveform analysis over a fixed timeperiod instead of cycle by cycle. For example, in some implementations,calculations are performed over 10-30 seconds and averaged to reduce theimpact of artifacts. Such averaging is possible for some metrics, suchas LVEDP, because they do not have very high beat-to-beat variability,at least within short time periods (e.g., ˜1 minute). Using multiplecycles allows the number of samples in the region of interest to beindependent of heart rate. Moreover, conglomerating multiplemeasurements can improve the resolution of phases of the cardiac cycle.Furthermore, effects of insufficient sampling can be further negated byincreasing the sampling period.

The systems, devices, and methods presented herein also detect suctionevents, which occur when a pump inlet is fully or partially occluded.Conventional suction detection systems are insufficiently sensitivity todetect minor suction events. In contrast, the systems, devices, andmethods presented herein can detect minor suction and when during thecardiac cycle the suction is occurring. These determinations may bebased on hysteresis of the motor current-aortic pressure curve. Thisimproved method can detect suction sooner and provide the user withinformation on how to prevent or decrease continued or worseningsuction. Furthermore, in some implementations, the systems, methods, anddevices can predict suction events by detecting an unfavorable cardiaccycle flow state which could lead to suction events.

FIG. 1 shows an exemplary prior art cardiac assist device located in aheart 102. The heart 102 includes a left ventricle 103, aorta 104, andaortic valve 105. The intravascular heart pump system includes acatheter 106, a motor 108, a pump outlet 110, a cannula 111, a pumpinlet 114, and a pressure sensor 112. The motor 108 is coupled at itsproximal end to the catheter 106 and at its distal end to the cannula111. The motor 108 also drives a rotor (not visible in figure) whichrotates to pump blood from the pump inlet 114 through the cannula 111 tothe pump outlet 110. The cannula 111 is positioned across the aorticvalve 105 such that the pump inlet 114 is located within the leftventricle 103 and the pump outlet 110 is located within the aorta 104.This configuration allows the intravascular heart pump system 100 topump blood from the left ventricle 103 into the aorta 104 to supportcardiac output.

The intravascular heart pump system 100 pumps blood from the leftventricle into the aorta in parallel with the native cardiac output ofthe heart 102. The blood flow through a healthy heart averages about 5liters/minute, and the blood flow through the intravascular heart pumpsystem 100 can be a similar or different flow rate. For example, theflow rate through the intravascular heart pump system 100 can be 0.5liters/minute, 1 liter/minute, 1.5 liters per minute, 2 liters/minute,2.5 liters/minute, 3 liters/minute, 3.5 liters/minute, 4 liters/minute,4.5 liters/minute, 5 liters/minute, greater than 5 liters/minute or anyother suitable flow rate.

The motor 108 of the intravascular heart pump system 100 can vary in anynumber of ways. For example, the motor 108 can be an electric motor. Therotor 108 can be operated at a constant rotational velocity to pumpblood from the left ventricle 103 to the aorta 104. Operating the motor108 to maintain a constant rotor speed generally requires supplying themotor 108 with varying amounts of current because the load on the motor108 varies during the different stages of the cardiac cycle of the heart102. For example, when the mass flow rate of blood into the aorta 104increases (e.g., during systole), the current required to operate themotor 108 increases. This change in motor current can thus be used tohelp characterize cardiac function as will be discussed further inrelation to the following figures. An electric motor current may bemeasured, or alternatively a magnetic field current may be measured.Detection of mass flow rate using motor current may be facilitated bythe position of the motor 108, which is aligned with the naturaldirection of blood flow from the left ventricle 103 into the aorta 104.Detection of mass flow rate using motor current may also be facilitatedby the small size and/or low torque of the motor 108. The motor 108 ofFIG. 1 has a diameter of about 4 mm, but any suitable motor diameter maybe used provided that the rotor-motor mass is small enough to beinfluenced by the inertia of pulsatile blood. The rotor-motor mass maybe influenced by the pulsatile mass flow of blood to produce adiscernable and characterizable effect on the motor parameter. In someimplementations, the diameter of the motor 108 is less than 4 mm.

In certain implementations, one or more motor parameters other thancurrent, such as power delivered to the motor 108, speed of the motor108, or electro-magnetic field are measured. In some implementations,the motor 108 in FIG. 1 operates at a constant velocity. In someimplementations, the motor 108 may be external to the patient and maydrive the rotor by an elongate mechanical transmission element, such asa flexible drive shaft, drive cable, or a fluidic coupling.

The pressure sensor 112 of the intravascular heart pump system 100 canbe an integrated component (as opposed to separate diagnostic catheter)and can be configured to detect pressure at various locations of thesystem 100 such as adjacent to a proximal end of the motor 108. Incertain implementations, the pressure sensor 112 of the intravascularheart pump system 100 can be disposed on the cannula 111, on thecatheter 106, on a portion of the system 100 external to the patient'sbody, or in any other suitable location. The pressure sensor 112 candetect blood pressure in the aorta 104 when the intravascular heart pumpsystem 100 is properly positioned in the heart 102, or for right heartsupport devices can detect pressure in the inferior vena cava (IVC) orthe pulmonary artery. The blood pressure information can be used toproperly place the intravascular heart pump system 100 in the heart 102.For example, the pressure sensor 112 can be used to detect whether thepump outlet has passed through the aortic valve 105 into the leftventricle 103 which would only circulate blood within the left ventricle103 rather than transport blood from the left ventricle 103 to the aorta104. The pressure sensor in FIG. 1 detects the absolute pressure at acertain point in the patient's vasculature, for example, in the aorta.In other embodiments, the pressure sensor detects absolute pressure inthe pulmonary artery or venous system. In other embodiments, thepressure sensor detects the pressure head or the delta pressure in thesystem, which can be equal to the aortic pressure less theleft-ventricular pressure.

In addition to aiding placement of the intravascular heart pump system100, one or more algorithms can be applied to the data obtained by thepressure sensor 112 in order to detect the cardiac phase of the heart102. For example, the data obtained by the pressure sensor 112 can beanalyzed to detect a dicrotic notch that indicates the beginning ofdiastolic filling. The dicrotic notch is a small downward deflection inthe arterial pulse or pressure contour immediately following the closureof the semilunar valves. This feature can be used as a marker for theend of systole or the ejection period. Because the measured pressurehead often contains more noise features than the measured motor current,the motor current can be used to ‘gate’ a period of time in which thedicrotic notch is likely to be identified, and the corresponding timeperiod of the measured pressure head can then be identified andanalyzed. Other features may also be detected as indicative of theLVEDP, for example, a change in the motor speed, the presence of anR-peak in ECG data, or changes in curvature or local slope of aparameter over time.

The intravascular heart pump system 100 can be inserted in various ways,such as by percutaneous insertion into the heart 102. For example, theintravascular heart pump system can be inserted through a femoral artery(not shown), through an axillary artery (not shown), through the aorta104, across the aortic valve 105, and into the left ventricle 103. Incertain implementations, the intravascular heart pump system 100 issurgically inserted into the heart 102. In some implementations, theintravascular heart pump system 100, or a similar system adapted for theright heart, is inserted into the right heart. For example, a rightheart pump similar to the intravascular heart pump system 100 can beinserted through the inferior vena cava, bypassing the right atrium andright ventricle, and extending into the pulmonary artery. In certainimplementations, the intravascular heart pump system 100 may bepositioned for operation in the vascular system outside of the heart 102(e.g., in the aorta 104). By residing minimally invasively within thevascular system, the intravascular heart pump system 100 is sufficientlysensitive to allow characterization of native cardiac function.Additionally, surgically implanted devices described below such asLVAD's would be sensitive to change in native cardiac function, althoughless sensitive that the intravascular heart pump 100.

FIG. 2 shows an exemplary prior art heart assist device 201 locatedoutside a heart 202. The heart 202 includes a left ventricle 203 and anaorta 204. The heart assist device 201 includes a motor 208, an inflowconduit 207, an outflow conduit 209, a first sensor 212 a, a secondsensor 212 b, a third sensor 212 c, and a catheter 206. The inflowconduit 207 is coupled at a first end 213 to a first side of the motor208 and at a second end 215 to an apex of the left ventricle 203. Theoutflow conduit 209 is coupled at a first end 217 to a second side ofthe motor 208 and at a second end 219 to the ascending aorta 204. Themotor 208 also drives a rotor (not visible in the figure) which rotatesto pump blood from the apex of the left ventricle 203 through the inflowconduit 207 into the outflow conduit 209 and to expel the blood into theaorta 204. The heart assist device 201 is configured to pump blood fromthe left ventricle 203 to the ascending aorta 204 to support cardiacoutput.

The heart assist device 201 pumps blood from the left ventricle 203 intothe aorta 204 bypassing the aortic valve (not visible in figure) andtransporting the blood through the inflow conduit 207 and the outflowconduit 209 around the heart 202, rather than within the heart 202. Theblood flow through the heart assist device 201 can deliver a similar orgreater flow rate than the flow rate of the prior art intravascularheart pump system 100 of FIG. 1. The heart assist device 201 can besurgically implanted in a patient such that the second end 219 of theoutflow conduit 209 and the second end 215 of the inflow conduit 207 aresurgically grafted to the heart 202 at the ascending aorta 204 and theleft ventricle 203, respectively. The motor 208 can be connected by adrive line (not shown) through a catheter 206 to a console (not shown)located outside the patient's body. The rotor (not shown) can run at aconstant, or substantially constant, speed. The power supplied to themotor 208 may be monitored at the console to determine a pump flow rateor other characteristics of the pump performance.

The first sensor 212 a, second sensor 212 b, and third sensor 212 c maybe similar to the pressure sensor 112 in FIG. 1. The sensors 212 a-c canbe pressure sensors used to determine blood pressure in the aorta 204 orblood pressure in the left ventricle 203, or may be placed to determinethe blood pressure and blood flow through the inflow conduit 207 andoutflow conduit 209. The blood pressure in the aorta 204 or the leftventricle 203 can be displayed to a user and/or can be used to determineoperating parameters of the heart assist device 201. The blood flow orpressure within the inflow conduit 207 and outflow conduit 209 can alsobe displayed to a user and used to monitor the heart assist device 201.The first sensor 212 a can also be a sensor of the pump motor 208 powerwhich can be used to determine a pump flow through the heart assistdevice 201.

FIG. 3 shows an illustrative heart pump system 300, according to certainimplementations, configured to estimate heart parameters indicative ofcardiac function. The heart pump system 300 may be similar to or thesame as the intravascular heart pump system 100 of FIG. 1 or the heartassist system 201 of FIG. 2. The heart pump system 300 may operatewithin a heart, partially within the heart, outside the heart, partiallyoutside the heart, partially outside the vascular system, or in anyother suitable location in a patient's vascular system. The heart pumpsystem 300 includes a heart pump 302 and a control system 304. All orpart of the control system 304 may be in a controller unitseparate/remote from the heart pump 302. In some implementations, thecontrol system 304 is internal to the heart pump 302. The control system304 and the heart pump 302 are not shown to scale.

The heart pump 302 can include a catheter 306, a motor 308, a rotor 310,and a pressure sensor 312. The motor 308 can be coupled to a distalregion of the catheter 306, and as mentioned previously, canalternatively be located outside of the patient's body and cancommunicate with the motor 308 via a drive shaft, drive cable, orfluidic connection. The motor 308 is also coupled to the rotor 310 suchthat operation of the motor 308 causes the rotor 310 to rotate and pumpblood. The pressure sensor 312 can be positioned along the catheter inany number of locations inserted into the patient's cardiovascularsystem such that that pressure sensor 312 can detect blood pressure whenthe heart pump 302 is inserted into a patient's vascular system. Inimplementations in which the heart pump 302 is an intravascular heartpump 302, such as the intravascular heart pump system 100 of FIG. 1, theheart pump 302 can be delivered to the left ventricle, and the pressuresensor 312 can sense aortic pressure when the intravascular heart pump302 is properly positioned in the left ventricle. In someimplementations, the pressure sensor 312 is positioned in a chamber orvessel separated by a valve from a chamber of interest. For example, thepressure sensor 312 may be positioned in the aorta when the rotor 310 ispositioned in the aorta, or the pressure sensor 312 may be positioned inthe inferior or superior vena cava with the rotor 310 while the outletof the pump is in the pulmonary artery. In some implementations, theheart system is configured such that the rotor 310 is positioned in theaorta when an inlet of the pump is placed in the left ventricle.

The control system 304 can include a controller 322, a current sensor314, and a heart parameter estimator 316. The controller 322 suppliescurrent to the motor 308 by an electrical connection 326 such as throughone or more electrical wires. The current supplied to the motor 308 viathe electrical connection 326 is measured by the current sensor 314. Theload that the motor 308 of a mechanical pump experiences is pressurehead, or the difference between the aortic and left ventricularpressure. The heart pump 302 experiences a nominal load during steadystate operation for a given pressure head, and variations from thisnominal load are a result of changing external load conditions, forexample the dynamics of left ventricular contraction. Changes to thedynamic load conditions alter the motor current required to operate therotor 310 at a constant, or substantially constant, speed. The motor mayoperate at a speed required to maintain the rotor 310 at a set speed. Asa result, the motor current drawn by the motor to maintain the rotorspeed can be monitored and used to understand the underlying cardiacstate. The cardiac state can be even more precisely quantified andunderstood by simultaneously monitoring the pressure head during thecardiac cycle using a pressure sensor 312 with regard to the motorcurrent to generate a hysteresis loop of quantitative pump performancethat may be visually assessed to determine changes in the cardiac stateand function. The heart parameter estimator 316 receives current signalsfrom the current sensor 314 as well as pressure signals from thepressure sensor 312. The heart parameter estimator 316 uses thesecurrent and pressure signals to characterize the heart's function. Theheart parameter estimator 316 may access stored look-up tables to obtainadditional information to characterize the heart's function based on thepressure and current signals. For example, the heart parameter estimator316 may receive an aortic pressure from the pressure sensor 312, andusing look-up tables, may use the aortic pressure to determine a deltapressure.

The controller 322 can store the current signals from the current sensor314 and the pressure signals from the pressure sensor 312 in a databasein a memory or server (not shown). The database and memory can beexternal to the controller 322 or included within the controller 322.The controller 322 can store the signals as arrays in the databasehaving particular associated addresses, and may also record time withthe signals. The controller 322 can also store determined cardiacparameters, such as LVEDP, in the memory for comparison to previouslystored cardiac parameters. The controller 322 accesses the hysteresiscurve by accessing an address of a database in the memory. Based on theaddress, the controller 322 selects a first array in which are stored aplurality of data points corresponding the measured motor parameter overtime. The controller 322 also selects a second array in which are storeda plurality of data points corresponding to the measured pressure orother physiological parameter over time. The controller 322 associatesthe first data points corresponding to the motor parameter with thesecond data points corresponding to the physiological parameter at eachpoint in time that a measurement was taken. The controller 322 may thendisplay the matched data points to a user on a screen or other displayas a hysteresis curve. Alternatively, the controller 322 can iteratedthrough the matched data points to calculate a cardiac parameter.

The heart parameter estimator 316 can characterize cardiac function anddetermine cardiac parameters according to two distinct methods. In afirst method, the heart parameter estimator 316 utilizes predeterminedpressure-current curves to extract information about cardiac functionand heart parameters. Using this method, the heart parameter estimator316 compares the power required to maintain a rotational speed of thepump rotor 310 and the pressure head, defined as the pressure gradientacross the pump, to predetermined performance curves which illustratethe power and pressure head as a function of the pump flow and topredetermined system curves relating the pressure head and motor current(predetermined pressure-current curves). Using the performance andsystem curves, the heart parameter estimator 316 characterizes the pumpbehavior in order to extract information about heart parameters andcardiac function.

In a second method, the heart parameter estimator 316 uses a best fitalgorithm to determine heart parameters related to cardiac function. Theheart parameter estimator 316 accesses a modified representation of pumpperformance from the pressure head as a function of the motor currentdraw. The motor current draw acts as a surrogate for the power or loadon the pump. The load on the pump at a given rotor RPM is determined bythe fluid motor torque described by the equation τ=H·d, where thetorque, τ, is determined by the pressure head, H, and volumetricdisplacement per revolution, d. Torque is directly related to the powerrequirements of the pump by the equation:

$P_{electrical} = {{V*I} = \frac{\tau*\omega}{\eta}}$where the electrical power requirement (P_(electrical)) is a product ofthe voltage (V) and current (I), and is related to the pump torque (τ),rotational speed (ω), and combined electrical and mechanical efficiency(η). Because the motor speed and efficiency are relatively constant andare known, the fluid motor torque can be determined from the electricalpower of the pump. The relation between the power and motor current mayvary according to pump design, but motor current is an operationallymeasured value for most pumps. The motor current is typically directlyrelated to the torque, and therefore to the load on the pump.

The pressure head is the load that the mechanical pump feels, and thepressure head is the difference between the aortic and left ventricularpressure, which changes throughout the cardiac cycle with the additionof the external flow of blood generated by cardiac contraction. Pumpoperation in the pulsatile environment of the heart alternates between asteady state ventricular filling and a ventricular ejection. The motorcurrent required to generate a specific RPM of the rotor is dependent onboth the pressure head and the cardiac state, and this results in ahysteresis loop as the motor experiences active cardiac contractionfollowed by ventricular filling during relaxation. The resulting motorcurrent hysteresis is a complete representation of the mechanical pumpperformance curve as it integrates the effects of external flow andpressure changes.

Classically, methods of measuring LVEDP have been indirect anddiscontinuous. One common method of measuring LVEDP is by using aSwan-Ganz catheter, in which the LVEDP is inferred through this catheterby wedging an inflated balloon into the pulmonary artery and using thepulmonary vasculature and the left atrium as a fluid column to obtainpressures in the left ventricle during diastole. This measurement isindirect and often includes significant measurement error, noise, andlack of reliability. Further, because the balloon in the pulmonaryartery cannot remain inflated, measurements are discontinuous. Analternative method that has historically been used to measure the LVEDPis to use a pressure transducer catheter that is inserted into the leftventricle of the heart. This captures the entire pulsatile pressurewaveform through a few cardiac cycles; but the catheter cannot remain inthe patient for extended periods or at the bedside. Other methods tonon-invasively predict the LVEDP have been developed using Dopplerechocardiogram or ultrasound. Unfortunately, they too are prone to thesame issues and cannot provide continuous pressure estimations overextended periods of time.

The LVEDP can be determined from the motor current drawn and pressurehead for a particular rotor speed. Assuming that the motor currentvariations corresponding to slight motor speed variations at enddiastole are linear, these variations can be corrected by linear scalingaccording to the equation:

$i_{c} = {i_{m}*\frac{\omega_{0}}{\omega}}$where the speed corrected motor current (i_(c)) is equal to the productof the measured motor current (i_(m)), and a ratio of the desired fixedmotor speed (ω₀) and real motor speed (ω). This is a safe assumption asmotor speed variation is minimal (±0.5%). The relationship between themotor current and the pressure head can be characterized, for example,by fitting an equation to the data. The speed corrected motor current(i_(c)) can be plotted against the measured pressure head and therelationship can then be fit to a high-order polynomial, for example byusing an R² optimization to produce a fourth order polynomial withpressure head as a function of motor current. Alternatively, any bestfit algorithm can be applied to the plot of the measured pressure headand the motor current in order to estimate the hysteresis loop. Forexample, the plot of the parameters can be fit to an ellipse or anangled or truncated ellipse to estimate the shape of the hysteresisloop. The equation determined by the best fit algorithm can then be usedto extract information about the cardiac function, for example, the LVPcan be extracted from an inflection point of the hysteresis curve, andthe phases of filling, relaxation, and ejection can be identified. Otherparameters can be determined from points on the hysteresis loop, thesize or shape of the hysteresis loop, changes in the size and shape ofthe hysteresis loop, local slope change, curvature change, or the areawithin the hysteresis loop. Further, coefficients for the fit can thenbe used to predict LVEDP for a given corrected motor current at a givenmotor RPM setting. These parameters enable a healthcare professional tobetter understand a current cardiac function of a patient and to provideappropriate cardiac support.

Other heart parameters indicative of cardiac function can also bedetermined by the heart parameter estimator 318 based on a comparison ofmeasured values to look-up tables or from the shape and values ofhysteresis loops formed from the measured motor parameters and pressureduring the cardiac cycle. For example, changes in contractility can berelated to the variation in slope of the pressure during contraction ofthe heart (dP/dt). The cardiac output is determined based on the flowrate of the blood through and past the pump. The stroke volume is anindex of left ventricular function which formula SV=CO/HR, where SV isthe stroke volume, CO is the cardiac output, and HR is the heart rate.Stroke work is the work done by the ventricle to eject a volume of bloodand can be calculated from the stroke volume according to the equationSW=SV*MAP, where SW is the stroke work, SV is the stroke volume, and MAPis the mean arterial pressure. Cardiac work is calculated by the productof stroke work and heart rate. Cardiac power output is a measure of theheart function in Watts calculated using the equation CPO=mAoP*CO/451,where CPO is the cardiac power output, mAoP is the mean aortic pressure,CO is the cardiac output, and 451 is a constant used to convertmmHG×L/min into Watts. The ejection fraction can be calculated bydividing the stroke volume by the volume of blood in the ventricle.Other parameters, such as chamber pressure, preload state, afterloadstate, heart recovery, flow load state, variable volume load state,and/or cardiac cycle flow state can be calculated from these values ordetermined by examination of the hysteresis loop.

An active catheter mounted heart pump within the left ventricle providesan avenue to direct and continuous LVEDP measurement during the mostcritical times, which is when the device would be in use. Withoutadditional intervention, this diagnostic measurement can be obtained byleveraging parameters from the device. In addition, this device canobtain diagnostic metrics that incorporate more than a single point inthe cardiac cycle. While useful, LVEDP remains only a single point oftime out of the entire cardiac cycle. More holistic metrics comprisingof information from the entire cardiac cycle can give more informationabout the state of the heart and be more representative of the actualstate of the heart.

The predetermined pressure-current curves can be measured using a mockcirculatory loop, animal data, or clinical data. For example, a mockcirculatory loop (MCL) with varying contractile, preload, and afterloadconditions may be used to define the bounds of pump performance, whilean animal model may be used to delineate biological variability andpathology. Using an MCL for characterization and animal models forvalidation is an effective means for relating performance of the heartpump 302 to heart function. Although baseline motor current may varybetween pumps, the current measurement from each pump can be normalizedto generate a normalized current waveform. In some implementations,heart pumps are binned separately in 30 mA ranges based on their currentresponses to normalize calculations for approximate flow rate.

The heart phase information may significantly improve the accuracy ofthe heart parameter estimator 316 by accounting for the effect ofhysteresis in the pressure-current curve. As will be discussed furtherbelow, the pressure-current curves may exhibit hysteresis due to thephases of the heart cycle. Therefore, to compare pressure and currentdata points accurately, the phase of the heart must be taken intoaccount. Otherwise, pressure and current data collected during systolemight be compared with non-analogous reference pressure and current datacollected during diastole, for example, which may skew the estimate ofthe heart parameter.

The estimation of the heart parameter by the heart parameter estimator316 can be continuous or nearly continuous while the heart pump 302 isimplanted in the heart. This can be advantageous over conventionalcatheter-based methods that only allow sampling of cardiac function atspecific times. For example, continuous monitoring may allow more rapiddetection of cardiac deterioration. Additionally, if the cardiac assistdevice is already in the patient, the cardiac function can be measuredwithout having to introduce an additional catheter into a patient.

After the heart parameter is estimated by the heart parameter estimator316, the heart parameter is output to the controller 322. The controller322, in turn, supplies a control signal for driving the motor 308. Insome implementations, the controller 322 operates the motor 308 at afixed set point. The set point may be a fixed rotational velocity orflow rate. For example, the controller may supply a varying voltage tohold a constant rotational velocity of the rotor 310 by the motor 308independent of pre-load and/or afterload. The controller 322 may alsoallow a user to vary the rotational velocity of the rotor 310, and insome implementations, the motor 308. For example, the user may select anew set point (e.g., by setting a new desired flow rate or rotationalspeed) or may select a time-varying input signal (e.g., a delta, step,ramp function, or sinusoid). In some implementations, the fixed setpoint may be an amount of power delivered to the motor 308. In certainimplementations, the heart parameter estimated by the heart parameterestimator 316 is displayed to a physician and the physician manuallyadjusts the set point of the motor at the controller 322.

The controller 322 can adjust the set point sent to the controller 322based on the heart parameter estimated by the heart parameter estimator316. For example, the degree/level of support (i.e., speed of the rotorand thus volumetric flow rate of blood delivered by the device) can beincreased when heart function is deteriorating or the degree of supportcan be decreased when heart function is recovering. This can allow thedevice to dynamically respond to changes in heart function to promoteheart recovery and to gradually wean a patient off of the therapy.

FIG. 4 shows a process 400 for determining a heart parameter indicativeof heart function. The process 400 can be performed using theintravascular heart pump system 100 of FIG. 1, the heart assist device201 of FIG. 2, the heart pump system 300 of FIG. 3, or any othersuitable heart pump. In step 402, the motor of a heart pump is operated.The motor may be operated at a rotational speed necessary to maintain aconstant or substantially constant rotational speed of the rotor. Instep 404, the current delivered to the motor is measured and the motorspeed is measured. The current may be measured using a current sensor(e.g., current sensor 314) or by any other suitable means. In step 406,the aortic pressure is measured. The aortic pressure may be measured bya pressure sensor coupled to the heart pump, by a separate catheter, bya noninvasive pressure sensor, or by any other suitable sensor. Thepressure sensor may be an optical pressure sensor, an electricalpressure sensor, a MEMS sensor, or any other suitable pressure sensor.In some implementations, ventricular pressure is measured in addition toor in alternative to measuring aortic pressure.

In some implementations, additional steps may be performed aftermeasuring the current delivered to the motor and the aortic pressure.For example, in some implementations, the aortic pressure may be scaledby a factor determined from a look-up table in order to find thedifferential pressure over time. In some implementations, the measuredcurrent and pressure data is smoothed in order to provide a less noisysignal.

In step 408, a segment of the hysteresis loop formed by the measuredcurrent delivered to the motor and measured aortic pressure isdetermined, corresponding to a phase of the heart. The segmentation andphase estimation can act as a filter for the pressure and currentsignals because it can allow pressure and current signals to be comparedto pressure and current signals that occurred during correspondingstages of the cardiac cycle. The segmentation and phase estimation maybe based on the pressure information received in step 406 and mayinvolve locating fiducial points in the pressure information indicativeof the heart phase. In some implementations, the dicrotic notch in thepressure signal is detected to indicate the beginning of diastolicfilling. The dicrotic notch is a small downward deflection in thearterial pulse or pressure contour immediately following the closure ofthe semilunar valves. This dicrotic notch can be used as a marker forthe end of systole and hence approximately the beginning of diastole.

In some implementations, the segmentation or phase estimation isentirely or partially based on ECG data. Such ECG data may be timed withthe pressure tracings. The characteristic in the ECG used to estimatethe heart phase may be the beginning of the QRS complex and the end ofthe T-wave. If there is noise in the ECG signal, it may be more reliableto detect the peak of the QRS complex (e.g., the R-wave) and the peak ofthe T-wave. The R-peak of the QRS waveform may also be used to identifytiming of various parameters, such as the time period in which the LVEDPwill be found, as the R-peak corresponds to the end cycle of thediastole. In phase estimation methods using either pressure signals orECG signals, an offset from the detected feature may be used to moreaccurately identify filling phases since actual filling occurs slightlybefore or after these identified landmarks. A combination of bothpressure signal-based and ECG-based methods can allow more reliableidentification of the heart phase. The weighting between the two methodscan be optimized using datasets having known filling time parameters,known left ventricular pressures, and high signal to noise ratios.

In addition to ECG data, the segmentation and heart phase estimation canalso be entirely or partially based on the motor parameter or a motorspeed, aortic pressure slope, respiratory variation, or any othersuitable physiological or device parameter. In some implementations, thesegmentation and heart phase estimation is determined based on anysingle one of these parameters or on a combination of any number ofthem.

In step 410, the hysteresis loop is mathematically described and theLVEDP is determined based on the mathematical description. Thehysteresis loop can be characterized by fitting an equation to the data,for example describing the loop by a polynomial function based onEuler's equation describing an ellipse, and the elliptical fit can beused to calculate the LVEDP. Mathematical fitting of the hysteresis loopadditionally enables the comparison of the size, shape and area of theloop or of segments of the loop over time, as well as analysis ofchanges in local slope or curvature of segments of the loop to measurechanges in cardiac parameters.

In some implementations, a look-up table is referenced to determine aheart parameter indicative of cardiac function based on the motorparameter, the pressure, and the heart phase. In some implementations,the table may embody predetermined pressure-current curves.

At step 412, a heart parameter is calculated. Determining the heartparameter can involve determining a point on the hysteresis loop basedon the mathematical fit, integrating the area of a section of thehysteresis loop, or mapping the measured current and pressure to heartparameters using look-up tables. The section of the hysteresis loop canbe segmented based on the Euler's equation elliptical fit and thebilateral line as will be described further with regard to FIG. 13, suchthat the ellipse consists of multiple segments each having at least onestraight edge. The segments can be translated and rotated, before beingintegrated by Riemann sums.

The heart phase information extracted from the hysteresis loop may bebinary (e.g., diastole or systole) or more fine-grained (e.g., systole,diastolic relaxation, and diastolic filling). The heart phase may be oneof cardiac ejection, diastolic filling, and diastolic relaxation. Thedetermined heart parameter can be contractility, stroke volume, ejectionfraction, chamber pressure, stroke work, cardiac output, cardiac poweroutput, left ventricular end diastolic pressure (LVEDP), preload state,afterload state, heart rate, heart recovery, flow load state, variablevolume load state, cardiac cycle volume load state, and/or cardiac cycleflow state. Left ventricular end diastolic pressure (LVEDP) is a singlepoint measurement that is often used by physicians to evaluate cardiachealth. LVEDP is significantly elevated in many cases of heart failure,indicating ventricular overload. This is largely due to a shift in theFrank-Starling relationship because of a change in the end diastolicpressure volume ratio (EDPVR). As patients move closer to heart failure,the Frank-Starling curve shifts downward, such that a given pressure(preload) results in a lower stroke volume. Because of this shift, at agiven cardiac output for a patient, the LVEDP can be indicative of thestate of the heart given all other conditions remain relativelyconstant. Measuring these changes in LVEDP can be valuable formonitoring the progression of the patient either towards heart failureor towards recovery thus allowing clinicians to adjust the requiredtherapy accordingly.

Alternatively, if a reference table is used, the look-up table mayaccept as its inputs pressure, motor current, and heart phase. Thepredetermined pressure-current curves can be measured using a mockcirculatory loop, animal data, or clinical data. For example, a mockcirculatory loop (MCL) with varying contractile, preload, and afterloadconditions may be used to define the bounds of pump performance, whilean animal model may be used to delineate biological variability andpathology. Using an MCL for characterization and animal models forvalidation is an effective means for relating performance of the heartpump to heart function. Although baseline motor current may vary betweenpumps, each pump can be normalized to generate a normalized currentwaveform.

The heart phase information from step 408 may significantly improve theaccuracy of the heart parameter estimation by accounting for the effectof hysteresis in the pressure-current curve. The pressure-current curvesexhibit hysteresis due to the phases of the heart cycle. Therefore, tocompare pressure and current data points accurately, the phase of theheart must be taken into account. Otherwise, pressure and current datacollected during systole might be compared with non-analogous referencepressure and current data collected during diastole, for example, whichmay skew the estimate of the heart parameter.

In step 414, the heart parameter is output. The output and/or thedetermination of the heart parameter can be continuous or nearlycontinuous while the heart pump is implanted in the heart. This can beadvantageous over conventional catheter-based methods that only allowsampling of cardiac function at specific times during the cardiac cycleor at discrete points in time. For example, continuous monitoring of theheart parameter may allow more rapid detection of cardiac deterioration.Continuous monitoring of the heart parameter can illustrate changes inthe heart condition over time, for example by outputting a continuoushysteresis parameter associated with the phases of the heart that mayshow differences as the condition of the heart changes. Additionally, ifthe cardiac assist device is already in the patient, the cardiacfunction can be measured without having to introduce an additionalcatheter into a patient. The heart parameter may be output using anysuitable user interface or report, such as the user interfaces describedbelow with regard to FIGS. 20A and 20B.

In some implementations, the power delivered to the motor is adjustedbased on the heart parameter. The power delivered to the motor can beadjusted automatically by a controller (e.g., controller 322) ormanually (e.g., by a healthcare professional). The degree of support canbe increased when a patient's heart function is deteriorating or thedegree of support can be decreased when a patient's heart function isrecovering, thus allowing the patient to be gradually weaned off of thetherapy. This can allow the device to dynamically respond to changes inheart function to promote heart recovery. It can also be used tointermittently modulate pump support and to diagnose how the heartreacts, e.g., if it can take over the pumping function from the heartpumping device.

FIG. 5 shows a process for calculating metrics of heart function andadjusting the level of support provided by a cardiovascular assistdevice. In step 502, a pump controller is operated. In step 504, ahysteresis parameter and the motor speed is measured. The hysteresisparameter may be a parameter of the heart pump's motor (e.g., motorcurrent or motor power). In step 506, a hemodynamic parameter ismeasured. For example, in some implementations, the aortic pressure ismeasured. In step 508, a look-up table of hemodynamic parameters as afunction of the hysteresis parameter is consulted or referenced in orderto determine the ΔP or differential pressure. An example look-up table2011 is show having a column “Hys. para” for stored values of thehysteresis parameter and a column “ΔP” for the pressure differencebetween the ventricle and the aorta. In some implementations, the tablemay be based on predetermined pressure-current curves. The heartparameter can be determined by mapping the measured current and pressureto heart parameters.

The predetermined pressure-current curves can be measured using a mockcirculatory loop, animal data, or clinical data. For example, a mockcirculatory loop (MCL) with varying contractile, preload, and afterloadconditions may be used to define the bounds of pump performance, whilean animal model may be used to delineate biological variability andpathology. Using an MCL for characterization and animal models forvalidation is an effective means for relating performance of the heartpump to heart function. Although baseline motor current may vary betweenpumps, each pump can be normalized to generate a normalized currentwaveform. In some implementations, heart pumps are binned separately in30 mA ranges based on their current responses to normalize calculationsfor approximate flow rate.

At step 510, the cardiac cycle phase is determined. This determinationof the cardiac cycle phase may be made using segmented spline curves. Aswill be discussed in relation to FIG. 13, segmented splines delineatethe regions of the total hysteresis loop. The hysteresis loop can besegmented into a known number of curve fitting splines. Each spline fitto a curve of the hysteresis loop is indicative of a cardiac cyclephase. For example, in a hysteresis loop fit with three splines, a firstspline may indicate a diastolic relaxation phase, a second spline mayindicate a diastolic filling, and a third spline may indicate thesystole. The meeting point of the second and third spline in this caseis the LVEDP. The phase estimation can act as a filter for the pressureand current signals because it can allow pressure and current signals tobe compared to pressure and current signals that occurred duringcorresponding stages of the cardiac cycle. The phase estimation may bebased on the pressure information received in step 2006 and may involvelocating fiducial points in the pressure information indicative of theheart phase. In some implementations, the dicrotic notch in the pressuresignal is detected to indicate the beginning of diastolic filling. Thedicrotic notch is a small downward deflection in the arterial pulse orpressure contour immediately following the closure of the semilunarvalves. This dicrotic notch can be used as a marker for the end ofsystole and hence approximately the beginning of diastole.

The heart phase information from step 510 may significantly improve theaccuracy of the heart parameter estimation by accounting for the effectof hysteresis in the pressure-current curve. Because thepressure-current curves exhibit hysteresis due to the phases of theheart cycle, to compare pressure and current data points accurately thephase of the heart must be taken into account. Otherwise, pressure andcurrent data collected during systole might be compared withnon-analogous reference pressure and current data collected duringdiastole, for example, which may skew the estimate of the heartparameter.

In step 512, a cardiac chamber pressure is output. In someimplementations, the cardiac chamber pressure measured is the pressureof the left ventricle. In certain implementations, the cardiac chamberpressure measured is the pressure of the right ventricle. In step 514, acoefficient of contractility is output. The contractility score providesan indication of cardiac function. More specifically, the contractilityscore represents the inherent strength and vigor of the heart'scontraction during systole. The stroke volume of the heart will begreater if the contractility of the heart is greater. For example,medium contractility may occur when the stroke volume of the heart isabout 65 mL. High contractility may occur when the stroke volume of theheart is over 100 mL. Low contractility may occur when the stroke volumeof the heart is less than 30 mL. The contractility score may beexpressed numerically and/or graphically. The contractility score may benon-dimensional. In step 516, the coefficient of volume load is output.In step 518, additional metrics of state are output.

In step 520, the cardiac chamber pressure determine in step 512 is usedto determine left ventricular end diastolic pressure (LVEDP). Thiscalculation may be made by determining the left ventricular pressurefrom step 512 corresponding to the end of diastole. LVEDP tends to besignificantly elevated in almost all cases of acute myocardialinfarction, especially with patients in heart failure. This is largelydue to a shift in the Frank-Starling relationship because of a change inthe end diastolic pressure volume ratio (EDPVR). As patients move closerto heart failure, the Frank-Starling curve shifts downward, such that agiven pressure results in a lower stroke volume. Because of this, at agiven cardiac output for a patient, the LVEDP can be indicative of thestate of the heart given all other conditions remain relativelyconstant. Measuring these changes in LVEDP can be valuable formonitoring the progression of the patient either towards heart failureor towards recovery thus allowing clinicians to adjust the requiredtherapy accordingly.

In step 522, the level of support provided by the assist device isassessed. In some implementations, this assessment is automatic. Incertain implementations, this assessment is at least partially performedby a healthcare professional. In some implementations, additionalinformation regarding the hemodynamic parameters and the level ofsupport are provided to allow a clinician to adjust the level of supportto optimize patient outcomes. In some implementations, the level ofsupport provided by the cardiovascular assist device is titrated bychanging the power delivered to the motor, changing the motor speed,and/or changing the flow rate, or any other suitable change that resultsin a change to the level of support by the cardiovascular assist device.In step 526, a patient heart assessment is output. This patient heartassessment may be shown on a user interface, such as user interface 2000of FIG. 20A or 2001 of FIG. 20B. In some implementations, the assessmentis a report that may be sent to a healthcare professional. In someimplementations, a recommendation for a level of support to be providedto the patient heart is output. In some implementations, the assessmentis a report that may be sent to a healthcare professional. Therecommendation of a level of support may be optimized to providehemodynamic support. The recommendation of a level of support may bebased on internal algorithms or tables. The recommendation of a level ofsupport may include directions to attain the recommended level ofsupport, including changing the volume flow delivery provided by thepump, changing the level (magnitude and/or frequency) of automatedpulsation based on quick speed changes, and/or changing the level ofpump speed (e.g., rotational speed of the motor or rotational speed ofthe rotor) in short or long bursts to provide augmented flow. In someimplementations, the process 500 of FIG. 5 may be repeated automaticallysuch that the process 500 provides closed loop control for the cardiacassist device. By titrating therapy to the patient's degree of need, therecovery of the heart can be promoted. If the assessment in step 526indicates that the heart has sufficiently recovered, the therapy may beterminated or a healthcare professional may be prompted to considerterminating therapy.

FIG. 6 shows a process 600 of determining LVEDP from a measured motorparameter signal and a sensor signal. The LVEDP can be calculatedaccording to one of several procedures. At step 602 a motor parameter isreceived over a period of time. As described herein, the measurement ofa motor parameter can include motor current, power, speed of the motor,or torque. At step 604, an input signal from the sensor is received overa period of time. The signal from the sensor may be any hemodynamicparameter, such as an aortic pressure. At step 606, a decision is madeas to whether to use an internal gating method.

If the decision is no, the process 600 follows path 607 to step 608 atwhich received ECG input 609 is used to gate the input hemodynamicparameter and motor parameter. The ECG input from step 609 is analyzedand a time period of the ECG data is identified in which the presence ofan inflection point that indicates an end cycle of diastole, or anR-peak in the QRS waveform, indicates that the LVEDP will be found inthe time period. The hemodynamic parameter measured in the correspondingtime period is then analyzed to find the point corresponding to theLVEDP. At step 610, the LVEDP is calculated from the identified pointusing a look-up table and the relationship between the hemodynamicparameter and the motor parameter is characterized by determining apolynomial function fit to the hemodynamic parameter and motorparameter.

If the decision at step 606 is that internal gating will be used, theprocess 600 follows path 611 to either step 612 or step 620 based on thedesired information from the data. Either pathway may be used todetermine the LVEDP, but additional cardiac parameters can also bedetermined from the pathway beginning from step 620.

At step 612, a time period of the motor parameter is identified in whichthere is a change in the motor parameter. This time period is considereda gating window, and the change in the motor parameter is indicative ofthe change in heart phase associated with LVEDP. In someimplementations, the change in the motor parameter may be a decrease inmotor speed due to a change in load, an increase in motor current due tothe change in load, or any other characteristic change in a motorparameter as a result of cardiac changes. At step 614 the identifiedtime period, or gating window is used to identify the corresponding timeperiod of the hemodynamic parameter in which the LVEDP is found. At step616, the LVEDP calculation inputs are identified in the hemodynamicparameter by analyzing the hemodynamic parameter data in the identifiedtime period and identifying a change in the hemodynamic parameter. Atstep 618, the LVEDP is calculated using a look-up table and a polynomialfunction.

At step 620, a hysteresis loop is formed from the motor parameter andsensor input and a polynomial algorithm which enables missing datapoints to be approximated. The data collected from the motor parameterand sensor input describe the phases of the heart in a hysteresis loop.For example, if the motor parameter is a motor current and the sensorinput is an aortic pressure, the polynomial algorithm allows thepressure head to be determined from the measured motor current andaortic pressure, such that a hysteresis loop can be created from themeasure motor current and the calculated pressure head. At step 622, anelliptical geometric fit to the hysteresis loop is generated, forexample using Euler's equation to fit the hysteresis loop to an ellipse.At step 624, the data forming the hysteresis loop is analyzed withregard to the elliptical fit to determine major point deviationindicative of an inflection point observed at the LVEDP value. At step626, the LVEDP point is calculated from the determined inflection pointusing a look-up table and a polynomial function. For example, theinflection point may be determined by analysis of the hysteresis loopformed from motor current and pressure head, and the LVEDP can becalculated from the pressure head data at the inflection point. TheLVEDP can then be output to a user, and additional heart metrics may bedetermined to aid in the understanding of the patient's cardiacfunction.

Gating algorithms as described above are applied to hemodynamicparameter data and pump or motor parameters in order to determine theLVEDP, cardiac cycle phase, and other parameters. In each of the abovepathways to the calculation of LVEDP, whether gating is internal orexternal, hemodynamic parameter data points identified using the gatingtechnique can be used with a look-up table, to look up the dynamic LVEDPcurve, and an LVEDP value may be outputted which may be used in thedetermination of other cardiac metrics. FIG. 7 shows a process forapplying a gating algorithm to determine LVEDP. The depicted processshows in greater detail the determination of the gating window andapplication of the gating algorithm to determine LVEDP, as describedwith regard to FIG. 6. Gating is used to determine or isolate thecardiac phases and/or left ventricular pressure (such as LVEDP). Thegating can be completed by examining the device parameter andphysiological parameters to locate local minima or maxima.

The controller measures a hysteresis parameter associated with thecardiac cycles and measures a device or motor parameter. The hysteresisparameter may be any cardiac hysteresis parameter discussed herein, andthe device parameter may be any device parameter which varies with timeand pulse. At step 702, the controller uses the input hysteresisparameter and device parameter to generate a gating window. The gatingalgorithm includes a method of means and standard deviations to identifythe data points which are relevant local minima by gating the data. Thelocal minima for the device parameter and the physiological parameterare determined independently, and the corresponding local minima datapoints are returned by the algorithm.

At step 704, the gating algorithm is applied to identify the LVEDP. Thecontroller inputs the local minima data points of the device parameterand the physiological parameter into a function which describes therelationship between the hysteresis device parameter (for example, motorcurrent) and the physiological parameter (for example, aortic pressure).The function is used to determine a point of the data associated withthe LVEDP.

At step 706, the calculated LVEDP point is used in a dynamic curvelook-up table to determine the LVEDP, and at step 708 the LVEDP isoutput from the system. The dynamic curve look-up table may translatethe aortic pressure measurement at a certain cardiac cycle to adifferential pressure in order to find the LVEDP value. Although FIG. 7shows LVEDP as the output of the gating algorithm, the gating algorithmmay be used with any metric calculation as described herein.

FIG. 8 shows a plot 800 of aortic pressure, left ventricular pressure,and motor current over time. The data from the plot of FIG. 8 can beused to generate pressure-current curves for estimation of a heartparameter (e.g., left ventricular pressure) from pressure and current.The plot 800 has an x-axis 802 in units of time and a y-axis 804 inunits of either pressure in mmHg or motor current in mA. The plot 800also includes an aortic pressure signal 806, a left ventricular pressuresignal 808, and a motor current signal 810. The aortic pressure signal806 can be measured by the pressure sensor 312 of FIG. 3, the pressuresensor 112 of FIG. 1, or any other suitable pressure sensor. The aorticpressure signal includes dicrotic notches 812 which can be used to markthe beginning of diastolic filling. The motor current signal 810 can begenerated from the current sensor 314 of FIG. 3 or any other suitablecurrent sensor. The left ventricular pressure signal 808 can begenerated using a dedicated catheter placed in the left ventricle, apressure sensor mounted on the inlet side of the pump, or an estimationbased on the pressure-current. The signals 806, 808, and 810 in plot 800can be generated from data collected in an animal model or in a humanpatient. The signals 806, 808, and 810 in the plot 800 were generatedfrom data collected in a pig heart while the pump motor was operating at33,000 rpm.

As shown in the plot 800, the motor current signal 810 varies with thecardiac phase. The load on the pump, and hence the motor current signal810, increases as the blood flow rate through the heart increases. Themotor current signal 810 increases at the same time as the leftventricular pressure signal 808 and the aortic pressure signal 806increases. This may seem counterintuitive since the pressure differenceacross the aortic valve is decreasing, but in this pump configuration,the prime determinant of the increasing current is increasing load onthe motor due to a higher mass flow rate. Higher mass flow rates occurduring systole, which leads to higher motor current during systole. Thisincrease in motor current is not apparent in the Bernoulli relation asconventionally expressed since the Bernoulli relation is often mass orrate normalized for describing a steady ohmic system. Unlike typicalpumping environments, the heart generates a phasic and dynamic load viaa variable mass flow to which the heart pump (e.g., heat pump 302)responds. This causes phasic components in the motor current signal thatdominates effects from changes in the pressure described by Bernoulli.As a result, the motor current waveform is representative of the cardiaccycle dynamics and can be used to extract cardiac energetics. Althoughthe motor driver may use a control algorithm that adjusts motor currentimmediately after a change in the heart phase, the effect of such acontrol algorithm on motor current can be predicted so that variationsin motor current can still be used as indicators of variations in theheart's contractile ability and stroke volume.

The motor current signal 810 can be used to extract the LVEDP from theleft ventricular pressure signal 808. Using an algorithm, the motorcurrent signal 810 is analyzed to determine the time period in which themotor current signal 810 changes. For example, the motor current signal810 falls precipitously between first time 811 and second time 813. Theleft ventricular pressure signal 808 can be analyzed at thecorresponding time period in order to accurately extract the LVEDP. Bygating the left ventricular pressure signal 808 based on the motorcurrent signal 810, the amount of data which needs to be analyzed tofind the LVEDP is cut down and noise is diminished. This gatingtechnique utilizing a change in the motor parameter can be used with avariety of motor parameters. For example, an increase in the motorcurrent indicating an increased load can indicate a time period in whichthe LVEDP may be identified. Additionally, a decrease in the motor speedin response to an increased load can also indicate the time period inwhich the LVEDP may be identified.

FIG. 9 shows a process 900 for applying an ECG-based gating algorithm todetermine LVEDP. The depicted process shows in greater detail thedetermination of the gating window using ECG data and application of thegating algorithm to determine LVEDP, as described with regard to FIG. 6.

Process 900 begins with a patient monitor 902 which measures and recordsECG data at step 904. The patient monitoring system 902 may be externalto the pump system or may be integrated within the pump system. Themeasured ECG data is transmitted to pump controller 906, where the ECGdata can be used ECG data to determine a gating window for identifyingLVEDP. At step 908, the pump controller generates an ECG-based gatingwindow by identifying the segment of ECG data in which the R-peak of theQRS waveform, or end cycle of the diastole is located. This may beaccomplished by fitting the data to a periodic equation and determiningdata points that deviate from the equation, or by identifying points inthe data which correspond to the R-peak. The gated window is a timeperiod in which the R-peak or end cycle of the diastole is found in theECG data, though the time period does not need to be expressed inabsolute time.

At step 910, the pump controller measures the aortic pressure and atstep 912, the pump controller measures the motor current. The ECG gatingwindow identified at step 908, and the measured aortic pressure andmotor current are used by the pump controller at step 914 to identify anLVEDP from the aortic pressure data. The controller analyzes the aorticpressure data points in the segment of the aortic pressure data thatcorresponds to the ECG gating window to determine the aortic pressurevalue at which the LVEDP is expressed. By gating the data, the LVEDPpoint may be more quickly determined and less data needs to be analyzed,decreasing the amount of processing time required.

At step 916, the pump controller accesses a dynamic curves look-up tableto convert the determined aortic pressure point to an actual LVEDP. Theactual LVEDP can be output from the gating algorithm for use by healthcare professionals. For example, health care professionals may makeadjustments to the pump speed by increasing or decreasing the pump speedbased on the reported LVEDP value.

In some implementations, cardiac cycle phase estimation is alsodetermined entirely or partially based on ECG data. Such ECG data may betimed with the pressure tracings. The characteristic in the ECG used toestimate the heart phase may be the beginning of the QRS complex and theend of the T-wave. If there is noise in the ECG signal, it may be morereliable to detect the peak of the QRS complex (e.g., the R-wave) andthe peak of the T-wave. In phase estimation methods using eitherpressure signals or ECG signals, an offset from the detected feature maybe used to more accurately identify filling phases since actual fillingoccurs slightly before or after these identified landmarks. The R-peakof the QRS waveform may also be used to identify a period in which aparticular cardiac parameter can be identified, such as the LVEDP, asthe R-peak corresponds to the end cycle of the diastole. A combinationof both pressure signal-based and ECG-based methods can allow morereliable identification. The weighting between the two methods can beoptimized using datasets having known filling time parameters, knownleft ventricular pressures, and high signal to noise ratios. In someimplementations, the phase estimation from a cardiac hysteresis loopcorresponds to one of cardiac ejection, diastolic filling, and diastolicrelaxation.

FIG. 10 shows a plot 1000 of LVEDP as measured and as predicted by MCLand animal models over time. The plot 1000 has an x-axis 1002 showingtime in units of seconds and a y-axis showing LVEDP in units of mmHg.The plot 1000 includes a first waveform 406, a second waveform 1008, anda third waveform 1010. The first waveform 1006 represents the LVEDP overtime as measured by a catheter in the left ventricle. The secondwaveform 1008 represents the LVEDP over time as predicted by analgorithm developed to characterize performance of a pump in a mockcirculatory loop (MCL). The third waveform 1010 represents the LVEDPover time as predicted by an algorithm developed to characterizeperformance of a pump in a porcine animal model. The inset plot 1012shows the correlation of the LVEDP as measured in the left ventricle andas predicted by the MCL and animal models for each measurement. Theinset plot 1012 has an x-axis 1014 showing the measured LVEDP in unitsof mmHg and a y-axis 1016 showing the predicted LVEDP in units of mmHg.The inset plot 1012 also includes a plurality of data points 1018representing measured-predicted pairs. The data points 1018 in plot 1012include unfilled points (for example 1020) representing pairs includingLVEDP as predicted by an animal-based algorithm, and star-shaped points(for example 1022) representing pairs including LVEDP as predicted by aMCL-based algorithm. The correlation line 1024 is provided to guide theeye and represents a 1 to 1 correlation, that is, predicted LVEDP equalto measured LVEDP.

Pump characterization was performed in both a MCL and in a porcineanimal model undergoing interventions to simulate disease. LVEDP wassuccessfully tracked during IVC occlusion in the animal and MCL models.The RMS error for the animal model was 0.90 mmHG. The RMS error for theMCL model was 0.35 mmHG. This suggests that the pump characterizationusing a MCL may be superior due to the presence of unidirectionalvariance versus bidirectional variance. Thus, using an MCL forcharacterization and animal models for validation can be an effectivemeans for relating performance of the heart pump to heart function. Datafrom MCL models and animal models may be used to develop predictivealgorithms and to develop predetermined pressure-current curves.

FIG. 11 shows a plot of the LVEDP calculated from patient dataillustrating the accuracy of the determined LVEDP using the gatingmethod. The plot 1100 includes an x-axis 1102 representing a number ofbeats of the heart and a y-axis 1104 representing the calculated LVEDPbased on the motor and physiological parameters. The plot 1100 includesa scatter plot 1103 of the calculated LVEDP at each beat of the heart, aline 1102 showing the reported pulmonary capillary wedge pressure(PCWP), and standard error lines 1101 for the reported PCWP line 1102.

The plot 1100 shows the PCWP 1102 actually recorded in a patient as wellas the LVEDP 1103 calculated by retrospectively applying the algorithmsto the patient data. The plot 1100 shows that the calculated LVEDP 1103is within the standard error lines 1101 for the reported PWCP line 1102.The PWCP is traditionally measured by wedging a pulmonary catheter andballoon into an arterial branch of the pulmonary artery. The calculatedLVEDP 1103 is closest to the reported PWCP 1102 at the data points takenat expiration of the patient, which is the same point at which the wedgepressure is taken in a patient. The calculated LVEDP 1103 as shown inFIG. 11 is comparable or better than the industry standard PWCP 1102when applied to patient data.

FIG. 12 shows a scatter plot 1200 of pressure head as a function ofmotor current. The plot 1200 demonstrates the effect of hysteresis onthe pressure-current curve. The plot 1200 has an x-axis 1202 showingcurrent in units of mA and a y-axis 1204 showing pressure head betweenthe left ventricle and the aorta in units of mmHg. The plot 1200 alsoincludes a plurality of data points 1206 representing current-pressurepairs gathered from a porcine animal model. The data points in plot 1200were generated while the motor was operating at 30,000 rpm. The datapoints 1206 roughly form a hysteresis loop. The shape of the scatterplot 1200 shows that the relationship between current and pressure headbetween the left ventricle and the aorta varies throughout the cardiaccycle. Because of the hysteresis in the pressure-current curve, a methodto gate measurements based on cardiac phase can help improve accuracy ofestimates of heart parameters by ensuring that sample data points arecompared with reference data points that occurred in the same heartphase (e.g., systole or diastole).

FIG. 13 shows a scatter plot 1300 of pressure head as a function ofmotor current. The plot 1300 has an x-axis 1302 showing current in unitsof mA and a y-axis 1304 showing pressure head between the left ventricleand the aorta in units of mmHg. The plot 1300 also includes a pluralityof data points 1306 representing current-pressure pairs. The data points1306 form a hysteresis loop and include segmented spline curves fit tothe hysteresis loop showing the determination of the phases of thecardiac cycle. The hysteresis loop is segmented into three curve fittingsplines, 1309, 1311 and 1313. Each of the splines is representative of acardiac cycle phase. The first spline 1309 is indicative of a section ofthe hysteresis loop recorded during diastolic relaxation (isovolumetricrelaxation). The second spline 1311 is indicative of a section of thehysteresis loop recorded during diastolic filling. The third spline 1313is indicative of a section of the hysteresis loop recorded duringsystole (ventricular contraction). The point at which the second spline1311 and the third spline 1313 meet is the LVEDP 1315. Thecharacteristic notch observed at the meeting of the second spline 1311and the third spline 1313 enables the identification of the LVEDP 1315point. The arrows 1307 and 1314 show the direction in which the cardiaccycles progress.

A characteristic notch can be observed at the time point at which LVEDPoccurs in the hysteresis loop, allowing for visual recognition of thepoint in the cardiac cycle, as well as algorithmic identification of theLVEDP as an inflection point in the pressure head and motor currenthysteresis loop. At the LVEDP inflection point, the motor currentchanges as the left ventricle goes from undergoing diastolic filling toactively contracting. Determination of the LVEDP inflection point fromthe hysteresis loop is dependent on the sampling rate for collection ofmotor and pressure parameters, and the calculation must take intoaccount sampling rate or extrapolate the data to accurately determinethe LVEDP inflection point. The phase estimation can act as a filter forthe pressure and current signals because it can allow pressure andcurrent signals to be compared to pressure and current signals thatoccurred during corresponding stages of the cardiac cycle.

The LVEDP 1315 point can also be calculated from the plot 1300 usingbest fit algorithms. The LVEDP 1315 point can be calculated from thehysteresis loop using polynomial equations and a best fit algorithmdescribing the hysteresis data as an ellipse. The hysteresis loop can beestimated using an equation based on Euler's equation for steady fluidmotion. The coefficients of the equation are calculated using multipleregression analysis from the equation:

$H = {{A*i} + {B*\frac{di}{dt}} + {C\;\omega^{2}} + {D*\frac{d^{2}i}{d^{2}t}}}$

where the coefficients are A, B, C, and D, i is the motor current, di/dtis a derivative of the motor current in time, ω is the thermodynamicwork, and d²i/d²t is a second derivative of the motor current in time.The final term in the equation is optional, as this term is very small.The final calculated equation describes the hysteresis loop and can beused to track changes in size and shape of the loop over time, orchanges in curvature or local slope over time, as well as used toextract metrics of heart function including the LVEDP.

According to the equation, an ellipse 1321 is fit to the hysteresis loopusing geometric methods, and the LVEDP 1315 point can be detected basedon the relationship of the data points to the described ellipse. Thedistance between each point and foci on the ellipse 1321 can be used todetermine outlier data points from the elliptical fit according to theequation:r ₁ +r ₂=2a

where r values are a distance from a point on the ellipse 1321 to eachfoci and a is the length of the short axis of the ellipse 1321. Thevalues of data points which are outside of the ellipse 1321 areevaluated for the location, and the most clustered location of datapoints is determined by iterating through the data. A cluster can bedefined in a variety of ways, for example a cluster can be defined as atleast 3 points which are within 2 mA and 1.5 mmHg of each other.

A bisecting line 1317 can be drawn through the ellipse 1321 describingthe hysteresis loop by algorithmically determining the clusters of thedata points 1306 forming the two ends of the hysteresis loop. Becausethe heart spends the largest amount of time in these two phases and onlytravels transiently between them, the majority of the measured datapoints 1306 are in these two locations. A first cluster 1318corresponding to peak relaxation and a second cluster 1319 correspondingto peak ejection are detected and a line 1317 is drawn between the meansof the two clusters 1318 and 1319. The line 1317 generally divides theellipse 1321 and the hysteresis data in half, into a top sectionincluding the first spline 1309 (diastolic relaxation) and correspondinggenerally higher pressure, and a bottom half generally corresponding toa higher pressure. The bottom section of the ellipse 1321 below the line1317 includes the second spline 1311 (diastolic filling) and the thirdspline 1313 (systole or ventricular contraction). The LVEDP 1315 pointcan be estimated from the elliptical fit of the data below the line 1317and determining the point which has the highest deviation from thecircle or ellipse 1321 fitted to the data. Additionally, other heartmetrics can be extracted from the data by segmenting the ellipseaccording to the cardiac phases and each segment can be numericallyintegrated with a Riemann sum. Alternatively, the hysteresis loop canalso be estimated using any other appropriate best fit algorithm.

Left ventricular diastolic pressure and left ventricular end diastolicpressure (LVEDP) can be used to determine the overall state of the heartfunction. LVEDP is the pressure in the left ventricle at the end ofventricular filling and immediately before ventricular contraction.LVEDP tends to be significantly elevated in almost all cases of acutemyocardial infarction, especially with patients in heart failure. Thisis largely due to a shift in the Frank-Starling relationship whichdescribes the relationship between the contractile state of the heartand the LVEDP because of a change in the end diastolic pressure volumeratio (EDPVR). As patients move closer to heart failure, theFrank-Starling curve shifts downward, such that a given pressure resultsin a lower stroke volume. Because of this shift, at a given cardiacoutput for a patient, the LVEDP can be indicative of the state of theheart given all other conditions remain relatively constant. Measuringthese changes in LVEDP can be valuable for monitoring the progression ofthe patient either towards heart failure or towards recovery, thusallowing clinicians to adjust the required therapy accordingly.

After the LVEDP point has been determined based on the elliptical fit,the actual LVEDP can be determined by accessing a look-up table.Predetermined pressure-current curves may be embodied in a look-up tablethat accepts as its inputs pressure, motor current, and heart phase. Theheart phase information may be binary (e.g., diastole or systole) ormore fine-grained (e.g., systole, diastolic relaxation, and diastolicfilling). The output of the look-up table can be other parametersbesides LVEDP, such as contractility, stroke volume, ejection fraction,chamber pressure, stroke work, cardiac output, cardiac power output,left ventricular end diastolic pressure (LVEDP), preload state,afterload state, heart rate, heart recovery, flow load state, variablevolume load state, cardiac cycle volume load state, and/or cardiac cycleflow state or any other suitable heart parameter, though the calculationof these parameters may require additional inputs.

While FIG. 13 shows a hysteresis curve formed from the data points 1306and a bisecting line 1317, this is to illustrate the principles of thealgorithm applied to the data. It is not necessary to actually create ordepict the hysteresis loop in order to extract the LVEDP data. Thecontroller can extract the LVEDP data by accessing and manipulatingarrays of stored data stored in the memory. The controller can store themeasured data in the memory and can characterize a relationship betweenthe measured aortic pressure and motor parameter, for example, byfitting the data with an equation that describes one parameter inrelation to the other such as an elliptical fit, Euler's equation, or apolynomial expression. The equation that characterizes the relationshipbetween the data points is then used to extract information about theLVEDP point, and in some implementations may also be used to extractinformation about additional cardiac parameters related to heartfunction.

Further, it is not necessary to record or measure motor and hemodynamicparameters for an entire cardiac cycle in order to extract the LVEDPdata. Enough data points at the transition from the diastolic fillingstage to the ventricular contraction phase of the cardiac cycle must becollected that the points can be fit to a portion of an elliptical curveand the LVEDP point which deviates from the elliptical fit can bedetermined. Alternatively, one or more cardiac cycles can be recorded inorder to accurately capture this portion of the curve.

In some implementations, it may be beneficial to display the hysteresisloop formed by relating the measured motor parameter and hemodynamicparameter to each other. The shape and size of the hysteresis loop, orthe changes in local slope or curvature, may provide important detailsabout the heart function of a patient. These can be used, for example,by a health care professional to make decisions related to patient care,such as whether to increase or decrease pump support by altering thespeed of the pump.

FIG. 14 shows a scatter plot 1400 of pressure head as a function of ahysteresis parameter after a hysteresis gate has been applied to segmentthe data. The plot 1400 has an x-axis 1402 which represents a hysteresisparameter and a y-axis 1404 that represents a pressure differencebetween the left ventricle and the aorta in units of mmHg. The data inthe plot 14 was gathered from a porcine animal model. The hysteresisparameter may be a motor parameter such as motor current expressed inmA. The hysteresis parameter may be a non-dimensional or normalizedparameter. The plot 1400 includes data points 1406 which have beensegments into three groups: a systole region 1408, a diastolic fillingregion 1410, and a diastolic relaxation region 1412. The region 1408corresponds to systole and includes data points 1409 that occurredduring systole. The region 1410 corresponds to diastolic filling andincludes data points 1411 that occurred during diastolic filling. Theregion 1412 corresponds to diastolic relaxation and includes data points1413 that occurred during diastolic relaxation. The data points 1406 maybe grouped into the systole region 1408, the diastolic filling region1410, and the diastolic relaxation region 1412 using a heart phaseestimator such as the heart phase estimator 318 of FIG. 3.

The plot 1400 also includes a subplot 1414 which has an x-axis 1416representing time and a y-axis 1418 representing aortic pressure. Thesubplot 1414 shows an aortic pressure signal 1420 having variousfiducial points 1422, 1424, 1426, and 1428 identified. The fiducialpoints 1422, 1424, and 1426, and 1428 can be used to segment the aorticpressure signal 1420 into phases of the cardiac cycle as indicated by asystole region 1430, a diastolic relaxation region 1432, and a diastolicfilling region 1434. The segmentation of the aortic pressure signal intothe regions 1430, 1432, and 1434 can be used to segment the data points1406 into the corresponding systole region 1408, diastolic relaxationregion 1412, and diastolic filling region 1410. Segmenting the data 1406into these regions allows like measurements to be compared so thatcomparisons are not biased due to misalignment of cardiac phases betweena sample measurement and a reference measurement. This can allow theestimation of the heart parameter to be robust to system hysteresis.

FIG. 15 shows a scatter plot 1500 of pressure head as a function ofmotor current. The plot 1500 has an x-axis 1502 showing a motorhysteresis parameter and a y-axis 1504 showing pressure head between theleft ventricle and the aorta in units of mmHg. The plot 1500 includes afirst hysteresis loop 1507 representing a baseline hysteresis and asecond hysteresis loop 1505 representing an example variation of thefirst hysteresis loop 1507. The second hysteresis loop 1505 includesmeasurable parameters determined from the plot 1500, including avariable hysteresis parameter 1515, a variable pressure head parameter1517, and a variable loop width parameter 1519. The variation in thesecond hysteresis loop 1505 may be caused by changes in the performanceof the heart in response to a medical event or in response to externalstimuli. The variable hysteresis parameter 1515, variable pressure headparameter 1517, and variable loop width parameter 1519 can describechanges between a first hysteresis loop 1507 and a second hysteresisloop 1505. The variable hysteresis parameter 1515 is measured along thex-axis 1502. The variable pressure head parameter 1517 is measured alongthe y-axis. The variable loop width parameter 1519 is a measure of thewidest portion of the hysteresis loop.

FIG. 16 shows a scatter plot 1600 of pressure head as a function ofmotor current before and after administration of a beta-blocker in aporcine animal model. The plot 1600 has an x-axis 1602 showing currentin units of mA and a y-axis 1604 showing pressure head between the leftventricle and the aorta in units of mmHg. The plot 1600 also includes aplurality of data points 1606 representing current-pressure pairs. Thedata points in plot 1600 were generated in a pig heart while the motorwas operating at 30,000 rpm. The data points 1606 roughly form a firsthysteresis loop 1607 and a second hysteresis loop 1605. The firsthysteresis loop 1607 has three regions, 1612, 1610, and 1608. The firstregion 1612 includes data points 1613 and is indicative of the diastolicrelaxation. The second region 1610 includes data points 1611 and isindicative of the diastolic filling. The third region 1608 includes datapoints 1609 and is indicative of systole. The first hysteresis loop 1607was generated during normal function of a heart. The second hysteresisloop 1605 was generated after administration of a beta-blocker. Thesecond hysteresis loop 1605 includes three regions 1616, 1618, and 1614.The first region 1616 includes data points 1615 and is indicative of thediastolic relaxation. The second region 1618 includes data points 1617and is indicative of the diastolic filling. The third region 1614includes data points 1619 and is indicative of systole. The shape of thescatter plot 1600 shows that the relationship between current andpressure head between the left ventricle and the aorta varies throughoutthe cardiac cycle and during normal function (as in hysteresis loop1607) and after administration of beta-blockers (as in hysteresis loop1605). The second hysteresis loop 1605 has a lower maximum differentialpressure than the first hysteresis loop 1607. Additionally, the shape ofthe second hysteresis loop 1605 is different than the shape of the firsthysteresis loop 1607. In particular, the first region 1616 of the secondhysteresis loop 1605 is shifted downward and has a less defined curvethan the corresponding first region 1612 of the first hysteresis loop1607. The third region 1614 of the second hysteresis loop 1605 is alsoshifted up relative to the corresponding third region 1608 of the firsthysteresis loop 1607. Further, the area enclosed by the first hysteresisloop 1607 is larger than the area enclosed by the second hysteresis loop1605. The administration of beta-blockers results in a change in thecontractility of the heart. A trained physician can use the shape of thedata points 1606 during a number of heart cycles, and the area of thehysteresis loop that the data points form, to determine morphologicalchanges in the heart as a result of the administration of beta-blockers,or to determine the level of heart failure.

FIG. 17 shows a smooth curve derived from the scatter plot of FIG. 16.Like the scatter plot 1600 in FIG. 16, the plot 1701 has an x-axis 1702showing current in units of mA and a y-axis 1704 showing pressure headbetween the left ventricle and the aorta in units of mmHg. The plot 1701shows three curves, a baseline curve 1709, a curve showing lowcontractility 1705, and a curve showing high contractility 1707. Thesmooth curves of FIG. 17 allow a healthcare professional to visualizethe changes in the behavior of the heart, for example after theadministration of beta-blockers, as in the low contractility state, andcan be used to extract meaningful cardiac parameters and changes inheart health. While FIGS. 16 and 17 include the hysteresis curves shownon an x-axis 1602 and 1702 of motor current in units of mA, thehysteresis curves may be plotted with any motor parameter which varieswith time and pulse on the x-axis.

FIG. 18A shows a scatter plot 1800 of pressure head as a function ofmotor current. The plot 1800 has an x-axis 1802 showing current in unitsof mA and a y-axis 1804 showing pressure head between the left ventricleand the aorta in units of mmHg. The plot 1800 also includes a pluralityof data points 1806 representing current-pressure pairs. The data points1806 form a first hysteresis loop 1808 and a second hysteresis loop1810. The shape of the scatter plot 1800 shows that the relationshipbetween current and pressure head between the left ventricle and theaorta varies throughout the cardiac cycle and during normal function (asin hysteresis loop 1808), and during transitioning of a myocardialinfarction (as in hysteresis loop 1810). The first hysteresis loop 1808is indicative of cycles of a heart prior to a myocardial infarction. Thesecond hysteresis loop 1810 is indicative of cycles of a heart during atransitioning myocardial infarction. The area enclosed by the secondhysteresis loop 1810 during the myocardial infarction is smaller thanthe area enclosed by the first hysteresis loop 1808. A trained physiciancan use the shape of the data points 1806 during a number of heartcycles to determine morphological changes in the heart during or after amyocardial infarction.

FIG. 18B shows a plot 1801 of the heart power index and the motorcurrent over a period of time. The plot 1801 has an x-axis 1803 showinga number of samples taken, a first y-axis 1805 showing the power indexof the heart, and a second y-axis 1807 showing an average motor currentin units of mA. The plot includes a first tracing 1812 of the heartpower index measured over the number of samples and a second tracing1810 of the motor current over the same samples. Heart power index is anew measure calculated from the hysteresis loop and is intended to givephysicians information regarding cardiac performance. In the plot 1801,the motor current 1810 remains largely constant over the measuredsamples. The heart power index 1808 is shown at low samples duringnormal cycles of the heart, labeled “pre-MI” 1814. At sample number 500,the heart power index 1812 decreases from about 3000 to about 2000during a myocardial infarction (labeled “MI”), indicating decreasedpumping performance of the heart. The heart power index is an indicatorthan can be used by trained physicians to monitor the performance of theheart during normal heart cycles and during and after events such asmyocardial infarction.

FIG. 19 shows examples of various cardiac parameters over timeillustrating the diagnostic capabilities afforded by visualizing theparameters. Each of the plots shows data generated from an animal modelshowing changes in the area index, contractility, flow load state, andmean aortic pressure over time. Plot I 1900 includes an x-axis 1903representing time in seconds, a first y-axis 1904 representing thenormalized index as a percent and a second y-axis 1905 representing meanpressure in mmHg. Plot I includes tracings of the area index 1910(indicative of overall heart function), contractility index 1908, flowload state 1912, and mean aortic pressure 1906 during a balloonocclusion of the inferior vena cava.

Plot II 1901 includes an x-axis 1913 representing time in seconds, afirst y-axis 1914 representing the normalized index as a percent, and asecond y-axis 1915 representing mean pressure in mmHg. Plot II includestracings of the area index 1920, contractility index 1918, flow loadstate 1922, and mean aortic pressure 1916 following the use of a betablocker.

Plot III 1902 includes an x-axis 1923 representing time in seconds, afirst y-axis 1924 representing the normalized index as a percent, and asecond y-axis 1925 representing mean pressure in mmHg. Plot III includestracings of the area index 1930, contractility index 1928, flow loadstate 1932, and mean aortic pressure 1926 following use of an inotrope.

The plots I-III of FIG. 19 illustrate the different responses in thevarious measurable cardiac parameters in response to various cardiacevents. For example, the decrease in heart function illustrated by thedecrease in the area index 1910 in plot I is preceded by a decrease inthe flow load state index 1912, indicating that there is a problem withthe volume of blood pumped by the heart. The decrease in the area index1920 in plot II coincides with the decrease of the contractility index1918, indicating that the beta blocker administered to the animal modelhas affected contractility of the heart. The cardiac parametersdisplayed in plots I-III can be calculated from hysteresis loops anddisplayed to illustrate changes in the contractility state, flow loadstate, and overall cardiac function, and to determine the cause of suchchanges.

Understanding the trends in the various cardiac parameters for a patientallows a trained medical professional to better address a patient'scardiac needs. The state of a patient's heart can be determined by ahealth care professional through the changes and trends in the variouscalculated cardiac parameters.

FIG. 20A shows an example user interface for a heart pump controllerthat includes a waveform of a metric of cardiac function over time. Theuser interface 2000 may be used to control the intravascular heart pumpsystem 100 of FIG. 1, the heart assist device 201 of FIG. 2, the heartpump system 300 of FIG. 3, or any other suitable heart pump. The userinterface 2000 includes a pressure signal waveform 2002, a motor currentwaveform 2004, a cardiac state waveform 2008, and a flow rate 2006. Thepressure signal waveform 2002 indicates the pressure measured by theblood pump's pressure sensor (e.g., pressure sensor 312). The pressuresignal waveform 2002 can be used by a healthcare professional toproperly place an intravascular heart pump (such as intravascular heartpump 100 in FIG. 1) in the heart. The pressure signal waveform 2002 isused to verify the position of the intravascular heart pump byevaluating whether the waveform 2002 is an aortic or ventricularwaveform. An aortic waveform indicates that the intravascular heart pumpmotor is in the aorta. A ventricular waveform indicates that theintravascular heart pump motor has been inserted into the ventriclewhich is the incorrect location. A scale 2014 for the placement signalwaveform is displayed to the left of the waveform. The default scalingis 0-160 mmHg. It can be adjusted in 20 mmHg increments. To the right ofthe waveform is a display 2003 that labels the waveform, provides theunits of measurement, and shows the maximum and minimum values and theaverage value from the samples received.

The motor current waveform 2004 is a measure of the energy intake of theheart pump's motor. The energy intake varies with the motor speed andthe pressure difference between the inlet and outlet areas of thecannula resulting in a variable volume load on the rotor. When used withan intravascular heart pump (such as intravascular heart pump 100 inFIG. 1), the motor current provides information about the catheterposition relative to the aortic valve. When the intravascular heart pumpis positioned correctly, with the inlet area in the ventricle and theoutlet area in the aorta, the motor current is pulsatile because themass flow rate through the heart pump changes with the cardiac cycle.When the inlet and outlet areas are on the same side of the aorticvalve, the motor current will be dampened or flat because the inlet andoutlet of the pump are located in the same chamber and there is novariability in differential pressure resulting in a constant mass flowrate, and subsequently constant motor current. A scale 2016 for themotor current waveform is displayed to the left of the waveform. Thedefault scaling is 0-1000 mA. The scaling may be adjustable in 100 mAincrements. To the right of the waveform is a display 2005 that labelsthe waveform, provides the units of measurement, and shows the maximumand minimum values and the average value from the samples received.Though the pressure sensor and motor current sensor may not be requiredfor positioning of surgically implanted pumps, such as heart assistdevice 201 of FIG. 2, the sensors can be used in such devices todetermine additional characteristics of native heart function to monitortherapy.

The cardiac state waveform 2008 is a display of the recorded cardiacstate over a period of time. The cardiac state may be displayed as aratio of the contractility of the heart divided by the volume of bloodpumped. The cardiac state may be calculated at discrete time points orcontinuously and displayed in the cardiac state waveform 2008 as a trendin order to provide a physician with an indicator of the currentperformance of the heart relative to the performance at other points intime in the patient's treatment. A scale 2018 for the cardiac statewaveform 2008 is displayed to the left of the cardiac state trend line.The default scaling is from 1-100 (unitless). The scaling may beadjusted to best show the cardiac state trend. To the right of thecardiac state waveform 2008 is a display 2007 that labels the trendline, provides additional information about the cardiac performance atthe current time, and shows the current values of contractility andvolume received from the pump. The display of this information as atrend line allows a physician to view the historical cardiac state of apatient and to make decisions based on the trend of the cardiac state.For example, a physician may observe from the cardiac state trend line adecline or an increase in the cardiac state over time and determine toalter or continue treatment based on this observation.

The flow rate 2006 can be a target blood flow rate set by the user or anestimated actual flow rate. In some modes of the controller, thecontroller will automatically adjust the motor speed in response tochanges in afterload to maintain a target flow rate. In someimplementations, if flow calculation is not possible, the controllerwill allow a user to set a fixed motor speed as indicated by speedindicator 2008.

FIG. 20B shows an example user interface 2001 for a heart pumpcontroller according to certain implementations. The user interface 2001may be used to control the intravascular heart pump system 100 of FIG.1, the heart assist device 201 of FIG. 2, the heart pump system 300 ofFIG. 3, or any other suitable heart pump. The user interface 2001includes a pressure signal waveform 2022, a motor current waveform 2024,a flow rate 2026, a speed indicator 2028, a contractility score 2030 anda metric of state score 2032. The pressure signal waveform 2022indicates the pressure measured by the blood pump's pressure sensor(e.g., pressure sensor 312). The pressure signal waveform 2022 can beused by a healthcare professional to properly place an intravascularheart pump (such as intravascular heart pump 100 in FIG. 1) in theheart. The pressure signal waveform 2022 is used to verify the positionof the intravascular heart pump by evaluating whether the waveform 2022is an aortic or ventricular waveform. An aortic waveform indicates thatthe intravascular heart pump motor is in the aorta. A ventricularwaveform indicates that the intravascular heart pump motor has beeninserted into the ventricle, which is the incorrect location. A scale2034 for the placement signal waveform is displayed to the left of thewaveform. The default scaling is 0-160 mmHg. It can be adjusted in 20mmHg increments. To the right of the waveform is a display 2033 thatlabels the waveform, provides the units of measurement, and shows themaximum and minimum values and the average value from the samplesreceived.

The motor current waveform 2024 is a measure of the energy intake of theheart pump's motor. The energy intake varies with the motor speed andthe pressure difference between the inlet and outlet areas of thecannula resulting in a variable volume load on the rotor. When used withan intravascular heart pump (such as intravascular heart pump 100 inFIG. 1), the motor current provides information about the catheterposition relative to the aortic valve. When the intravascular heart pumpis positioned correctly, with the inlet area in the ventricle and theoutlet area in the aorta, the motor current is pulsatile because themass flow rate through the heart pump changes with the cardiac cycle.When the inlet and outlet areas are on the same side of the aorticvalve, the motor current will be dampened or flat because the inlet andoutlet of the pump are located in the same chamber and there is novariability in differential pressure resulting in a constant mass flowrate, and subsequently constant motor current. A scale 2036 for themotor current waveform is displayed to the left of the waveform. Thedefault scaling is 0-1000 mA. The scaling may be adjustable in 100 mAincrements. To the right of the waveform is a display 2025 that labelsthe waveform, provides the units of measurement, and shows the maximumand minimum values and the average value from the samples received.Though the pressure sensor and motor current sensor may not be requiredfor positioning of surgically implanted pumps, such as heart assistdevice 201 of FIG. 2, the sensors can be used in such devices todetermine additional characteristics of native heart function to monitortherapy.

The flow rate 2026 can be a target flow rate set by the user or anestimated actual flow rate. In some modes of the controller, thecontroller will automatically adjust the motor speed in response tochanges in afterload to maintain a target flow rate. In someimplementations, if flow calculation is not possible, the controllerwill allow a user to set a fixed motor speed as indicated by speedindicator 2028.

The contractility score 2030 provides an indication of cardiac function.More specifically, the contractility score represents the inherentstrength and vigor of the heart's contraction during systole. The strokevolume of the heart will be greater if the contractility of the heart isgreater. For example, medium contractility may occur when the strokevolume of the heart is about 65 mL. High contractility may occur whenthe stroke volume of the heart is over 100 mL. Low contractility mayoccur when the stroke volume of the heart is less than 30 mL. Thecontractility score may be expressed numerically and/or graphically. Thecontractility score may be non-dimensional. Changes in contractility canbe determined from the variation in slope of pressure during cardiaccontraction (dP/dt). The metric of state score 2032 also provides anindication of cardiac function. The metric of state score may be anindication of volume load, the pressure of a cardiac pressure, oranother metric of cardiac function.

The position, depictions of the metrics on the controller, and theidentification and number of metrics and recommendations in FIGS. 20Aand 20B are meant to be illustrative. The number of metrics andindicators, position of same metrics and indicators on the console andthe metrics displayed may be varied from those shown here. The metricsdisplayed to a user can be contractility, stroke volume, ejectionfraction, chamber pressure, stroke work, cardiac output, cardiac poweroutput, LVEDP, preload state, afterload state, flow load state, variablevolume load state, cardiac cycle volume load state, cardiac cycle flowstate, heart rate, and/or heart recovery as defined by any or all of theprior heart related parameters, the trends over time, and specificthresholds, or any other suitable metric derived from a hysteresisparameter associated with a cardiac assist device placed in or partiallyin an organ of a patient.

FIG. 21 shows a process for detecting suction in an intravascular heartpump and determining the cause of the suction. Suction occurs when aninlet of the cardiac assist device is occluded (e.g., by a valve leafletor other anatomical structure) or when blood volume or preload to theventricle is reduced and less than the output of the selected pumpspeed. Preventing suction can allow intravascular cardiac assist devicesto operate safely at higher flow rates. Conventional suction detectiontechnology is insufficiently sensitive to detect minor suction, todetect when the suction is occurring during the cardiac cycle, and todetect an unfavorable cardiac cycle flow state which could lead tosuction events. The process 2100 may detect suction sooner thanconventional methods and can provide the user information on how toprevent continued or worsening suction.

In step 2102, pressure is detected from the cardiac assist device. Instep 2104, rotor speed and motor current are detected. In step 2106, thecardiac cycle phase is determined. The phase estimation can act as afilter for the pressure and current signals because it can allowpressure and current signals to be compared to pressure and currentsignals that occurred during corresponding stages of the cardiac cycle.The phase estimation may be based on the pressure information receivedin step 2102 and may involve locating fiducial points in the pressureinformation indicative of the heart phase. In some implementations, thedicrotic notch in the pressure signal is detected to indicate thebeginning of diastolic filling. The dicrotic notch is a small downwarddeflection in the arterial pulse or pressure contour immediatelyfollowing the closure of the semilunar valves. This dicrotic notch canbe used as a marker for the end of systole and hence approximately thebeginning of diastole.

In some implementations, the phase estimation is entirely or partiallybased on ECG data. Such ECG data may be timed with the pressuretracings. The characteristic in the ECG used to estimate the heart phasemay be the beginning of the QRS complex and the end of the T-wave. Ifthere is noise in the ECG signal, it may be more reliable to detect thepeak of the QRS complex (e.g., the R-wave) and the peak of the T-wave.In phase estimation methods using either pressure signals or ECGsignals, an offset from the detected feature may be used to moreaccurately identify filling phases since actual filling occurs slightlybefore or after these identified landmarks. A combination of bothpressure signal-based and ECG-based methods can allow more reliableidentification. The weighting between the two methods can be optimizedusing datasets having known filling time parameters, known leftventricular pressures, and high signal to noise ratios.

In step 2108, predetermined pressure curves are referenced to determinea heart parameter indicative of suction. In some implementations, thetable may be based on predetermined pressure-current curves. Heartparameters can be determined by mapping the measured current andpressure to heart parameters. The reference table may be a look-up tablethat accepts as its inputs: pressure, motor current, and heart phase.The heart phase information may be binary (e.g., diastole or systole) ormore fine-grained (e.g., systole, diastolic relaxation, and diastolicfilling). In step 2110, a suction event is detected. The suction eventcan be detected by determining a deviation from the normal predeterminedpressure-current curves. The deviation may indicate a mass flow ratethat is atypically low for the corresponding aortic pressure and heartphase. In some implementations, the suction event is detected by achange in a hysteresis loop of a motor parameter and a pressure head. Anearly indication of a suction event is the collapse of the hysteresisloop. The loop collapses as the volume load decreases, indicating that asuction event has begun.

In step 2112, the time in the cardiac cycle during which the suctionevents occur is determined. For example, it may be determined whethersuction events occur during systole or diastole. The method for stoppingthe suction event or events can depend on whether the suction eventoccurs during systole or diastole. In step 2114, the coefficient ofvolume load is determined. Based on the coefficient of volume load andthe determination of when the suction occurs in the cardiac cycle, theroot cause of suction is determined. For example, the root cause may besuction against a valve leaflet. In step 2118, a user is provided withcorrective actions for addressing the suction event. For example, theuser may be prompted to reposition the cardiac assist device within theheart. In some implementations, when onset of a suction event isdetected an early detection warning of possible suction event isactivated.

In some implementations, conditions leading to a suction event can bedetected, for example, by detecting a reduction in the volume loadexperienced by the pump. The chamber blood volume of the pump may bedetected using the hysteresis in the measurement of the motor parameterand pressure measurement at the pressure sensor and compared to a setlevel of pump support to determine if the chamber blood volume iscritically reduced. Critical reduction of chamber blood volume can bepresent when a suction event is occurring, and detection of a reductioncan provide an early warning or a prompt to action to prevent a suctionevent from continuing. In some implementations, the action is automated.In some implementations, the action is recommended. In someimplementations, the automated or recommended action is to reducesupport level provided by the pump (e.g., decrease rotor speed) to matchthe volume status.

Example Embodiment 1

An IMPELLA® percutaneous heart pump (Abiomed, Inc., Danvers, Mass.) wasimplanted in a mock circulatory loop (MCL) consisting of ventricle andaorta with pressures measured throughout. The IMPELLA® operated atvarious performance levels and MCL fluid dynamic profiles while motorcurrent was recorded. An LVP prediction algorithm was generated usingpump characterization. Performance was validated in an anesthetized pigwith an implanted IMPELLA®. Ischemia-like or hemorrhagic shock-likeevents were induced by balloon-occluding the left anterior descendingcoronary artery or the inferior vena cava respectively. The IMPELLA®pump's motor current and pressure signals in the pulmonary artery, leftventricle, and aorta were recorded simultaneously.

At minimal ventricular support, ischemia and shock was followed within 4minutes by profound changes. Instability and shock were reflected bychanges in the motor current waveform. The left ventricular pressure(LVP) was predicted during hemorrhagic shock with characterization fromboth the MCL (RMS error ˜0.3 mmHg) and the pig (RMS error ˜0.9 mmHg). Incontrast, at maximal ventricular support, there was no hemodynamiccompromise and the motor current remained intact after >20 minutes ofocclusion.

The results indicate coupling between heart and device function. Withoutadequate support, heart performance reduced and led to hemodynamiccollapse, which was tracked by the LVP algorithm. Success of thealgorithm is due to the use of the MCL and the porcine model duringdevelopment. The MCL defined the bounds of pump performance, while theanimal delineated biological variability and pathology. This unifiedapproach can be an effective means of defining performance of anydevice: using MCL for characterization and animals as validation.

The foregoing is merely illustrative of the principles of thedisclosure, and the apparatuses can be practiced by other than thedescribed embodiments, which are presented for purposes of illustrationand not of limitation. It is to be understood that the apparatusesdisclosed herein, while shown for use in percutaneous insertion of heartpumps, may be applied to apparatuses in other applications.

Variations and modifications will occur to those of skill in the artafter reviewing this disclosure. The disclosed features may beimplemented, in any combination and subcombination (including multipledependent combinations and subcombinations), with one or more otherfeatures described herein. The various features described or illustratedabove, including any components thereof, may be combined or integratedin other systems. Moreover, certain features may be omitted or notimplemented.

In general, embodiments of the subject matter and the functionaloperations described in this specification can be implemented in digitalelectronic circuitry, or in computer software, firmware, or hardware,including the structures disclosed in this specification and theirstructural equivalents, or in combinations of one or more of them.Embodiments of the subject matter described in this specification can beimplemented as one or more computer program products, i.e., one or moremodules of computer program instructions encoded on a computer readablemedium for execution by, or to control the operation of, data processingapparatus. The computer readable medium can be a machine-readablestorage device, a machine-readable storage substrate, a memory device, acomposition of matter affecting a machine-readable propagated signal, ora combination of one or more of them. The term “data processingapparatus” encompasses all apparatus, devices, and machines forprocessing data, including by way of example a programmable processor, acomputer, or multiple processors or computers. The apparatus caninclude, in addition to hardware, code that creates an executionenvironment for the computer program in question, e.g., code thatconstitutes processor firmware, a protocol stack, a database managementsystem, an operating system, or a combination of one or more of them. Apropagated signal is an artificially generated signal, e.g., amachine-generated electrical, optical, or electromagnetic signal that isgenerated to encode information for transmission to suitable receiverapparatus.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, and it can bedeployed in any form, including as a stand-alone program or as a module,component, subroutine, or other unit suitable for use in a computingenvironment. A computer program does not necessarily correspond to afile in a file system. A program can be stored in a portion of a filethat holds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random access memory or both. The essential elements of a computer area processor for performing instructions and one or more memory devicesfor storing instructions and data. Generally, a computer will alsoinclude, or be operatively coupled to receive data from or transfer datato, or both, one or more mass storage devices for storing data, e.g.,magnetic, magneto optical disks, or optical disks. However, a computerneed not have such devices.

Examples of changes, substitutions, and alterations are ascertainable byone skilled in the art and could be made without departing from thescope of the information disclosed herein. All references cited hereinare incorporated by reference in their entirety and made part of thisapplication.

We claim:
 1. A heart pump system comprising: a catheter; a motor; arotor operatively coupled to the motor; and a pump housing at leastpartially surrounding the rotor so that actuating the motor drives therotor and pumps blood through the pump housing; a sensor configured todetect a hemodynamic parameter over time; and a controller configuredto: detect over time a motor parameter associated with the motor,receive an input from the sensor of the detected hemodynamic parameterover time, determine a relationship between the detected hemodynamicparameter and the detected motor parameter, characterize therelationship between the hemodynamic parameter and the motor parameterusing a polynomial best fit algorithm, store the determined relationshipin a memory, determine a cardiac cycle phase from the relationshipbetween the hemodynamic parameter and the motor parameter, obtain ahysteresis curve based on the relationship between the hemodynamicparameter and the motor parameter, and select a sample time on thehysteresis curve corresponding to the cardiac cycle phase.
 2. The heartpump system of claim 1, wherein the motor parameter is current deliveredto the motor, power delivered to the motor, or motor speed.
 3. The heartpump system of claim 1, wherein the controller is further configured todetermine at least one cardiovascular metric by extracting an inflectionpoint, a local slope change, or a curvature change from thecharacterized relationship between the detected hemodynamic parameterand the motor parameter.
 4. The heart pump system of claim 3, whereinthe at least one cardiovascular metric is at least one of contractility,stroke volume, ejection fraction, chamber pressure, stroke work, cardiacoutput, cardiac power output, left ventricular pressure, preload state,afterload state, heart rate, heart recovery, flow load state, variablevolume load state, cardiac cycle volume load state, or cardiac cycleflow state.
 5. The heart pump system of claim 4, wherein the at leastone cardiovascular metric is the left ventricular end diastolic pressure(LVEDP).
 6. The heart pump system of claim 5, wherein the hemodynamicparameter is aortic pressure, the motor parameter is current, andwherein characterizing the relationship includes fitting an equation toat least a portion of data representing the measured current and apressure head calculated from the measured current and the aorticpressure.
 7. The heart pump system of claim 6, the controller furtherconfigured to: determine, from the equation fit to at least a portion ofthe data representing the measured current and pressure head, an LVEDPpoint; and access a look-up table to determine an actual LVEDP valuefrom the LVEDP point in the pressure head data.
 8. The heart pump systemof claim 7, wherein determining an LVEDP point includes identifying thechange in slope, the change in curvature or the inflection point in theequation fit to at least a portion of the current and the pressure head.9. The heart pump system of claim 1, wherein determining the cardiaccycle phase further comprises: detecting that the cardiac cycle phase isin diastolic relaxation when the sample time corresponds to a segment ofthe hysteresis curve corresponding to an increasing pressure head; ordetecting that the cardiac cycle phase is in diastolic filling when thesample time corresponds to a segment of the hysteresis curvecorresponding to a decreasing pressure head following diastolicrelaxation to a point distinguished by a rapid change in slope orcurvature, or identification of the inflection point; or detecting thatthe cardiac cycle phase is in systole when the sample time correspondsto a segment of the hysteresis curve having a decreasing pressure headfrom the inflection point to a minimum pressure head.
 10. The heart pumpsystem of claim 1, wherein the motor parameter and hemodynamic parameterare detected over a portion of a cardiac cycle.
 11. The heart pumpsystem of claim 1, wherein the motor parameter and hemodynamic parameterare detected over one or more cardiac cycles.
 12. The heart pump systemof claim 1, wherein the motor is configured to maintain a substantiallyconstant speed of the rotor during actuation of the rotor.
 13. The heartpump system of claim 1, wherein the controller is further configured tostore the at least one cardiovascular metric in a memory with apreviously determined at least one cardiovascular metric.
 14. The heartpump system of claim 1, comprising an integrated motor positioned nearthe distal end of the catheter proximate the heart pump.
 15. A heartpump system comprising: a catheter; a motor; a rotor operatively coupledto the motor; a pump housing at least partially surrounding the rotor sothat actuating the motor drives the rotor and pumps blood through thepump housing, and a pressure sensor configured to detect an aorticpressure over time; and a controller configured to: detect a motorparameter over time, receive the aortic pressure over time from thesensor, store a relationship between the motor parameter and the aorticpressure in the memory; determine a time period in which an inflectionpoint of a curve based on the relationship is found, wherein theinflection point is indicative of LVEDP, and identify the inflectionpoint of the curve based on the determined time period.
 16. The heartpump system of claim 1, wherein the controller is configured to adjust,based on the relationship, operation of the heart pump system to changethe driving of the rotor.
 17. The heart pump system of claim 1, whereinthe controller is further configured to: display an indicator of thedetermined relationship; receive a request for adjustment of operationof the heart pump system, and adjust, based on the request, operation ofthe motor to drive the heart pump system.
 18. The heart pump system ofclaim 15, wherein determining a time period in which the inflectionpoint indicative of LVEDP is found includes identifying a time period inwhich the received motor parameter changes.
 19. The heart pump system ofclaim 18, the controller further configured to determine LVEDP based onthe inflection point from a dynamic curve look-up table in the memory.20. The heart pump system of claim 18, wherein the controller is furtherconfigured to receive an ECG signal, and wherein determining a timeperiod in which an inflection point indicative of LVEDP is foundincludes identifying a time period in which the ECG signal indicates anend cycle of diastole.
 21. The heart pump system of claim 15, whereinthe controller is further configured to determine from the storedrelationship at least one heart metric, and wherein the heart metric isat least one of contractility, stroke volume, ejection fraction, chamberpressure, stroke work, cardiac output, cardiac power output, leftventricular pressure, preload state, afterload state, heart rate, heartrecovery, flow load state, variable volume load state, cardiac cyclevolume load state, or cardiac cycle flow state.
 22. The heart pumpsystem of claim 15, wherein the motor parameter is one of motor current,change in motor current, variability of motor current, and a netintegrated area of motor current and pressure.
 23. The heart pump systemof claim 15, the controller further configured to determine a cardiaccycle phase from the relationship between the motor parameter and theaortic pressure, wherein the cardiac cycle phase is determined using oneor more of ECG data, a hemodynamic parameter, the motor parameter andthe motor speed, and/or a slope of the aortic pressure.
 24. The heartpump system of claim 15, wherein the motor is configured to maintain asubstantially constant rotor speed during actuation of the rotor. 25.The heart pump system of claim 15, wherein the heart pump furthercomprises an integrated motor sized and configured for insertion into apatient's vasculature.